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Dissertations / Theses on the topic 'Human face recognition (Computer science) Image processing'
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Feng, Guo Can. "Face recognition using virtual frontal-view image." HKBU Institutional Repository, 1999. http://repository.hkbu.edu.hk/etd_ra/267.
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Da, Silva Sandro Cahanda Marinho. "Remote surveillance and face tracking with mobile phones (smart eyes)." Thesis, University of the Western Cape, 2005. http://etd.uwc.ac.za/index.php?module=etd&.
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This thesis addresses analysis, evaluation and simulation of low complexity face detection algorithms and tracking that could be used on mobile phones. Network access control using face recognition increases the user-friendliness in human-computer interaction. In order to realize a real time system implemented on handheld devices with low computing power, low complexity algorithms for face detection and face tracking are implemented. Skin color detection algorithms and face matching have low implementation complexity suitable for authentication of cellular network services. Novel approaches for reducing the complexities of these algorithms and fast implementation are introduced in this thesis. This includes a fast algorithm for face detection in video sequences, using a skin color model in the HSV (Hue-Saturation-Value) color space. It is combined with a Gaussian model of the H and S statistics and adaptive thresholds. These algorithms permit segmentation and detection of multiple faces in thumbnail images. Furthermore we evaluate and compare our results with those of a method implemented in the Chromatic Color space (YCbCr). We also test our test data on face detection method using Convolutional Neural Network architecture to study the suitability of using other approaches besides skin color as the basic feature for face detection. Finally, face tracking is done in 2D color video streams using HSV as the histogram color space. The program is used to compute 3D trajectories for a remote surveillance system.
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鄭健城 and Kin-shing Dominic Cheng. "Studies on facial surface reconstruction from image correspondence." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31224131.
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Cheng, Kin-shing Dominic. "Studies on facial surface reconstruction from image correspondence." Hong Kong : University of Hong Kong, 2000. http://sunzi.lib.hku.hk/hkuto/record.jsp?B22925958.
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Man, Chun Him. "Human face image searching system with relevance feedback using sketch." HKBU Institutional Repository, 2005. http://repository.hkbu.edu.hk/etd_ra/618.
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Li, Qi. "An integration framework of feature selection and extraction for appearance-based recognition." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file 8.38 Mb., 141 p, 2006. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:3220745.
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Gökçay, Didem. "Self-organizing features for regularized image standardization." [Gainesville, Fla.] : University of Florida, 2001. http://purl.fcla.edu/fcla/etd/ank7112.
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Thesis (Ph. D.)--University of Florida, 2001.Title from first page of PDF file. Document formatted into pages; contains ix, 117 p.; also contains graphics. Vita. Includes bibliographical references (p. 109-116).
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Zhang, Cuiping Cohen Fernand S. "3D face structure extraction from images at arbitrary poses and under arbitrary illumination conditions /." Philadelphia, Pa. : Drexel University, 2006. http://hdl.handle.net/1860/1294.
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Zhan, Ce. "Facial expression recognition for multi-player on-line games." School of Computer Science and Software Engineering, 2008. http://ro.uow.edu.au/theses/100.
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Multi-player on-line games (MOGs) have become increasingly popular because of the opportunity they provide for collaboration, communications and interactions. However, compared with ordinary human communication, MOG still has several limitations, especially in the communication using facial expressions. Although detailed facial animation has already been achieved in a number of MOGs, players have to use text commands to control the expressions of avatars. This thesis proposes an automatic expression recognition system that can be integrated into a MOG to control the facial expressions of avatars. To meet the specific requirements of such a system, a number of algorithms are studied, tailored and extended. In particular, Viola-Jones face detection method is modified in several aspects to detect small scale key facial components with wide shape variations. In addition a new coarse-to-fine method is proposed for extracting 20 facial landmarks from image sequences. The proposed system has been evaluated on a number of databases that are different from the training database and achieved 83% recognition rate for 4 emotional state expressions. During the real-time test, the system achieved an average frame rate of 13 fps for 320 x 240 images on a PC with 2.80 GHz Intel Pentium. Testing results have shown that the system has a practical range of working distances (from user to camera), and is robust against variations in lighting and backgrounds.
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Chen, Xiaochen. "Tracking vertex flow on 3D dynamic facial models." Diss., Online access via UMI:, 2008.
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Rosato, Matthew J. "Applying conformal mapping to the vertex correspondence problem for 3D face models." Diss., Online access via UMI:, 2007.
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Wei, Xiaozhou. "3D facial expression modeling and analysis with topographic information." Diss., Online access via UMI:, 2008.
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Wagener, Dirk Wolfram. "Feature tracking and pattern registration." Thesis, Stellenbosch : Stellenbosch University, 2003. http://hdl.handle.net/10019.1/53424.
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Thesis (MScEng) -- Stellenbosch University, 2003.ENGLISH ABSTRACT: The video-based computer vision patient positioning system that is being developed at iThemba Laboratories, relies on the accurate, robust location, identification and tracking of a number of markers on the patient's mask. The precision requirements are demanding - a small error in the location of the markers leads to an inaccurate positioning of the patient, which could have fatal consequences. In this thesis we discuss the contsruction of suitable markers, their identification with subpixel accuracy, as well as a robust tracking algorithm. The algorithms were implemented and tested on real data. We also note and give examples of other applications, most notably 2D human face tracking and the 3D tracking of a moving person.
AFRIKAANSE OPSOMMING: Die video-gebaseerde rekenaarvisie pasiënt posisionerings stelsel wat by iThemba Laboratoriums ontwikkel word, maak staat op die akkurate opsporing, identifikasie en volging van 'n stel merkers op die pasiënt se masker. Die akkuraatheids voorwaardes is besonders streng - selfs 'n klein fout in die lokasie vandie merkers sal lei tot die onakkurate posisionering van die pasiënt, wat dodelike gevolge kan hê. In hierdie tesis bespreek ons die konstruksie van geskikte merkers, die identifikasie van die merkers tot op subbeeldingselement vlak en ook die akkurate volging van die merkers. Die algoritmes is op regte data getoets. Ander toepassings soos 2D en 3D menlike gesigs-volging word ook kortliks bespreek.
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Ndlangisa, Mboneli. "DRUBIS : a distributed face-identification experimentation framework - design, implementation and performance issues." Thesis, Rhodes University, 2004. http://eprints.ru.ac.za/93/1/MNdlangisa-MSc.pdf.
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We report on the design, implementation and performance issues of the DRUBIS (Distributed Rhodes University Biometric Identification System) experimentation framework. The Principal Component Analysis (PCA) face-recognition approach is used as a case study. DRUBIS is a flexible experimentation framework, distributed over a number of modules that are easily pluggable and swappable, allowing for the easy construction of prototype systems. Web services are the logical means of distributing DRUBIS components and a number of prototype applications have been implemented from this framework. Different popular PCA face-recognition related experiments were used to evaluate our experimentation framework. We extract recognition performance measures from these experiments. In particular, we use the framework for a more indepth study of the suitability of the DFFS (Difference From Face Space) metric as a means for image classification in the area of race and gender determination.
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Akinbola, Akintunde A. "Estimation of image quality factors for face recognition." Morgantown, W. Va. : [West Virginia University Libraries], 2005. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=4308.
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Thesis (M.S.)--West Virginia University, 2005.Title from document title page. Document formatted into pages; contains vi, 56 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 52-56).
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Chen, Shaokang. "Robust discriminative principal component analysis for face recognition /." [St. Lucia, Qld.], 2005. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe18934.pdf.
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Bartlett, Marian Stewart. "Face image analysis by unsupervised learning and redundancy reduction /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 1998. http://wwwlib.umi.com/cr/ucsd/fullcit?p9907603.
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Le, Hung Son. "Face Recognition : A Single View Based HMM Approach." Doctoral thesis, Umeå : Department of Applied Physics and Electronics, Umeå University, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-1485.
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Lee, Jinho. "Synthesis and analysis of human faces using multi-view, multi-illumination image ensembles." Columbus, Ohio : Ohio State University, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1133366279.
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Brennan, Victor L. "Principal component analysis with multiresolution." [Gainesville, Fla.] : University of Florida, 2001. http://etd.fcla.edu/etd/uf/2001/ank7079/brennan%5Fdissertation.pdf.
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Thesis (Ph. D.)--University of Florida, 2001.Title from first page of PDF file. Document formatted into pages; contains xi, 124 p.; also contains graphics. Vita. Includes bibliographical references (p. 120-123).
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Tepvorachai, Gorn. "An Evolutionary Platform for Retargetable Image and Signal Processing Applications." Case Western Reserve University School of Graduate Studies / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=case1209504058.
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Spasic, Nemanja. "Anomaly Detection and Prediction of Human Actions in a Video Surveillance Environment." Thesis, University of Cape Town, 2007. http://pubs.cs.uct.ac.za/archive/00000449/.
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World wide focus has over the years been shifting towards security issues, not in least due to recent world wide terrorist activities. Several researchers have proposed state of the art surveillance systems to help with some of the security issues with varying success. Recent studies have suggested that the ability of these surveillance systems to learn common environmental behaviour patterns as wells as to detect and predict unusual, or anomalous, activities based on those learnt patterns are possible improvements to those systems. In addition, some of these surveillance systems are still run by human operators, who are prone to mistakes and may need some help from the surveillance systems themselves in detection of anomalous activities. This dissertation attempts to address these suggestions by combining the fields of Image Understanding and Artificial Intelligence, specifically Bayesian Networks, to develop a prototype video surveillance system that can learn common environmental behaviour patterns, thus being able to detect and predict anomalous activity in the environment based on those learnt patterns. In addition, this dissertation aims to show how the prototype system can adapt to these anomalous behaviours and integrate them into its common patterns over a prolonged occurrence period. The prototype video surveillance system showed good performance and ability to detect, predict and integrate anomalous activity in the evaluation tests that were performed using a volunteer in an experimental indoor environment. In addition, the prototype system performed quite well on the PETS 2002 dataset 1, which it was not designed for. The evaluation procedure used some of the evaluation metrics commonly used on the PETS datasets. Hence, the prototype system provides a good approach to anomaly detection and prediction using Bayesian Networks trained on common environmental activities.
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Paleari, Marco. "Informatique Affective : Affichage, Reconnaissance, et Synthèse par Ordinateur des Émotions." Phd thesis, Télécom ParisTech, 2009. http://pastel.archives-ouvertes.fr/pastel-00005615.
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L'informatique Affective regarde la computation que se rapporte, surgit de, ou influence délibérément les émotions et trouve son domaine d'application naturel dans les interactions homme-machine a haut niveau d'abstraction. L'informatique affective peut être divisée en trois sujets principaux, à savoir: l'affichage,l'identification, et la synthèse. La construction d'une machine intelligente capable dinteragir'de façon naturelle avec son utilisateur passe forcement par ce trois phases. Dans cette thèse nous proposions une architecture basée principalement sur le modèle dite "Multimodal Affective User Interface" de Lisetti et la théorie psychologique des émotions nommé "Component Process Theory" de Scherer. Dans nos travaux nous avons donc recherché des techniques pour l'extraction automatique et en temps-réel des émotions par moyen des expressions faciales et de la prosodie vocale. Nous avons aussi traité les problématiques inhérentes la génération d'expressions sur de différentes plateformes, soit elles des agents virtuel ou robotique. Finalement, nous avons proposé et développé une architecture pour des agents intelligents capable de simuler le processus humaine d'évaluation des émotions comme décrit par Scherer.
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Viswavarapu, Lokesh Kumar. "Real-Time Finger Spelling American Sign Language Recognition Using Deep Convolutional Neural Networks." Thesis, University of North Texas, 2018. https://digital.library.unt.edu/ark:/67531/metadc1404616/.
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This thesis presents design and development of a gesture recognition system to recognize finger spelling American Sign Language hand gestures. We developed this solution using the latest deep learning technique called convolutional neural networks. This system uses blink detection to initiate the recognition process, Convex Hull-based hand segmentation with adaptive skin color filtering to segment hand region, and a convolutional neural network to perform gesture recognition. An ensemble of four convolutional neural networks are trained with a dataset of 25254 images for gesture recognition and a feedback unit called head pose estimation is implemented to validate the correctness of predicted gestures. This entire system was developed using Python programming language and other supporting libraries like OpenCV, Tensor flow and Dlib to perform various image processing and machine learning tasks. This entire application can be deployed as a web application using Flask to make it operating system independent.
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Dantcheva, Antitza. "Biométries faciales douces : méthodes, applications et défis." Phd thesis, Télécom ParisTech, 2011. http://pastel.archives-ouvertes.fr/pastel-00673146.
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Cette thèse s'intéresse aux biométries dites douces, et notamment à leurs utilisations en termes de sécurité, dans le cadre de différents scénarii commerciaux, incluant des aspects usage. L'accent sera ainsi porté sur les caractéristiques faciales qui constituent un jeu de traits significatifs de l'apparence physique mais aussi comportementale de l'utilisateur permettant de différencier, classer et identifier les individus. Ces traits, qui sont l'âge, le sexe, les cheveux, la peau et la couleur des yeux, mais aussi la présence de lunettes, de moustache ou de barbe, comportent plusieurs avantages notamment la facilité avec laquelle ils peuvent être acquis, mais également du fait qu'ils correspondent à la façon dont les êtres humains perçoivent leurs environnements. Plus précisément, les traits issus de la biométrie douce sont compatibles avec la manière dont l'humain tend à catégoriser son entourage, une démarche impliquant une structuration hiérarchique des différents traits. Cette thèse explore ces différents traits et leurs applications dans les systèmes de biométries douces (SBS), et met l'accent sur la manière dont de tels systèmes peuvent atteindre des buts différents, y compris la recherche accélérée dans des bases de données, l'identification et la ré-identification d'individus, mais également la prédiction et la quantification de l'esthétique d'un visage. Ce travail est motivé notamment par l'importance croissante de ces applications dans notre société en constante évolution, mais aussi par le côté peu contraignant du système. En effet, les SBS sont généralement non-intrusifs, et nécessitent le plus souvent de faibles temps de calculs, permettant ainsi une analyse biométrique rapide, sans imposer obligatoirement l'accord et la coopération de l'individu. Ces atouts rendent la biométrie douce indispensable dans les applications qui ont besoin de traitement d'images ou de vidéos en temps réel.
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Costello, Anthony. "Facilitating Information Retrieval in Social Media User Interfaces." Doctoral diss., University of Central Florida, 2014. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/6257.
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As the amount of computer mediated information (e.g., emails, documents, multi-media) we need to process grows, our need to rapidly sort, organize and store electronic information likewise increases. In order to store information effectively, we must find ways to sort through it and organize it in a manner that facilitates efficient retrieval. The instantaneous and emergent nature of communications across networks like Twitter makes them suitable for discussing events (e.g., natural disasters) that are amorphous and prone to rapid changes. It can be difficult for an individual human to filter through and organize the large amounts of information that can pass through these types of social networks when events are unfolding rapidly. A common feature of social networks is the images (e.g., human faces, inanimate objects) that are often used by those who send messages across these networks. Humans have a particularly strong ability to recognize and differentiate between human Faces. This effect may also extend to recalling information associated with each human Face. This study investigated the difference between human Face images, non-human Face images and alphanumeric labels as retrieval cues under different levels of Task Load. Participants were required to recall key pieces of event information as they emerged from a Twitter-style message feed during a simulated natural disaster. A counter-balanced within-subjects design was used for this experiment. Participants were exposed to low, medium and high Task Load while responding to five different types of recall cues: (1) Nickname, (2) Non-Face, (3) Non-Face & Nickname, (4) Face and (5) Face & Nickname. The task required participants to organize information regarding emergencies (e.g., car accidents) from a Twitter-style message feed. The messages reported various events such as fires occurring around a fictional city. Each message was associated with a different recall cue type, depending on the experimental condition. Following the task, participants were asked to recall the information associated with one of the cues they worked with during the task. Results indicate that under medium and high Task Load, both Non-Face and Face retrieval cues increased recall performance over Nickname alone with Non-Faces resulting in the highest mean recall scores. When comparing medium to high Task Load: Face & Nickname and Non-Face significantly outperformed the Face condition. The performance in Non-Face & Nickname was significantly better than Face & Nickname. No significant difference was found between Non-Faces and Non-Faces & Nickname. Subjective Task Load scores indicate that participants experienced lower mental workload when using Non-Face cues than using Nickname or Face cues. Generally, these results indicate that under medium and high Task Load levels, images outperformed alphanumeric nicknames, Non-Face images outperformed Face images, and combining alphanumeric nicknames with images may have offered a significant performance advantage only when the image is that of a Face. Both theoretical and practical design implications are provided from these findings.Ph.D.
Doctorate
Industrial Engineering and Management Systems
Engineering and Computer Science
Industrial Engineering
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Aghaei, Maedeh. "Social Signal Processing from Egocentric Photo-Streams." Doctoral thesis, Universitat de Barcelona, 2018. http://hdl.handle.net/10803/650918.
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Wearable photo-cameras offer a hands-free way to record images from the camera- wearer perspective of daily experiences as they are lived, without the necessity to interrupt recording due to the device battery or storage limitations. This stream of images, known as egocentric photo-streams, contains important visual data about the living of the user, where social events among them are of special interest. Social interactions are proven to be a key to longevity and having too few interactions equates the same risk factor as smoking regularly. Considering the importance of the matter, there is no wonder that automatic analysis of social interactions is largely attracting the interest of the scientific community.
Analysis of unconstrained photo-streams however, imposes novel challenges to the social signal processing problem with respect to conventional videos. Due to the free motion of the camera and to its low temporal resolution, abrupt changes in the field of view, in illumination condition and in the target location are highly frequent. Also, since images are acquired under real-world conditions, occlusions occur regularly and appearance of the people undergoes intensive variations from one event to another.
Given a user wearing a photo-camera during a determined period, this thesis, driven by the social signal processing paradigm presents a framework for comprehensive social pattern characterization of the user. In social signal processing, the second step after recording the scene is to track the appearance of multiple people who are involved in the social events. Hence, our proposal begins by introducing a multi-face tracking which holds certain characteristics to deal with challenges imposed by the egocentric photo-streams. Next step forward in social signal processing, is to extract the so-called social signals from the tracked people. In this step, besides the conventionally studied social signals, clothing as a novel social signal is proposed for further studies within the social signal processing. Finally, the last step is social signal analysis, itself. In this thesis, social signal analysis is essentially defined as reaching an understanding of social patterns of a wearable photo-camera user by reviewing captured photos by the worn camera over a period of time. Our proposal for social signal analysis is comprised of first, to detect social interactions of the user where the impact of several social signals on the task is explored. The detected social events are inspected in the second step for categorization into different social meetings. The last step of the framework is to characterize social patterns of the user. Our goal is to quantify the duration, the diversity and the frequency of the user social relations in various social situations. This goal is achieved by the discovery of recurrences of the same people across the whole set of social events related to the user.
Each step of our proposed pipeline is validated over relevant datasets, and the obtained results are reported quantitatively and qualitatively. For each section of the pipeline, a comparison with related state-of-the-art models is provided. A discussion section over the obtained results is also given which is dedicated to highlighting the advantages, shortcomings, and differences of the proposed models, and with regards to the state-of-the-art.Las cámaras portables ofrecen una forma de capturar imágenes de experiencias diarias vividas por el usuario, desde su propia perspectiva y sin la intervención de éste, sin la necesidad de interrumpir la grabación debido a la batería del dispositivo o las limitaciones de almacenamiento. Este conjunto de imágenes, conocidas como secuencias de fotos egocéntricas, contiene datos visuales importantes sobre la vida del usuario, donde entre ellos los eventos sociales son de especial interés. Las interacciones sociales han demostrado ser clave para la longevidad, el tener pocas interacciones equivale al mismo factor de riesgo que fumar regularmente. Teniendo en cuenta la importancia del asunto, no es de extrañar que el análisis automático de las interacciones sociales atraiga en gran medida el interés de la comunidad científica. Sin embargo, el análisis de secuencias de fotos impone nuevos desafíos al problema del procesamiento de las señales sociales con respecto a los videos convencionales. Debido al movimiento libre de la cámara y a su baja resolución temporal, los cambios abruptos en el campo de visión, en la iluminación y en la ubicación del objeto son frecuentes. Además, dado que las imágenes se adquieren en condiciones reales, las oclusiones ocurren con regularidad y la apariencia de las personas varía de un evento a otro. Dado que un individuo usa una cámara fotográfica durante un período determinado, esta tesis, impulsada por el paradigma del procesamiento de señales sociales, presenta un marco para la caracterización integral del patrón social de dicho individuo. En el procesamiento de señales sociales, el segundo paso después de grabar la escena es rastrear la apariencia de varias personas involucradas en los eventos sociales. Por lo tanto, nuestra propuesta comienza con la introducción de un seguimiento de multiples caras que posee ciertas características para hacer frente a los desafíos impuestos por las secuencias de fotos egocéntricas. El siguiente paso en el procesamiento de señales sociales es extraer las señales sociales de las personas bajo análisis. En este paso, adema´s de las señales sociales estudiadas convencionalmente, en esta tesis se propone la vestimenta como una nueva señal social para estudios posteriores dentro del procesamiento de señales sociales. Finalmente, el último paso es el análisis de señales sociales. En esta tesis, el análisis de señales sociales se define esencialmente como la comprensión de los patrones sociales de un usuario de cámara portable, mediante la revisión de fotos capturadas por la cámara llevada durante un período de tiempo. Nuestra propuesta para el análisis de señales sociales se compone de diferentes pasos. En primer lugar, detectar las interacciones sociales del usuario donde se explora el impacto de varias señales sociales en la tarea. Los eventos sociales detectados se inspeccionan en el segundo paso para la categorización en diferentes reuniones sociales. El último paso de la propuesta es caracterizar los patrones sociales del usuario. Nuestro objetivo es cuantificar la duración, la diversidad y la frecuencia de las relaciones sociales del usuario en diversas situaciones sociales. Este objetivo se logra mediante el descubrimiento de apariciones recurrentes de personas en todo el conjunto de eventos sociales relacionados con el usuario. Cada paso de nuestro método propuesto se valida sobre conjuntos de datos relevantes, y los resultados obtenidos se evalúan cuantitativa y cualitativamente. Cada etapa del modelo se compara con los trabajos relacionados más recientes. También, se presenta una sección de discusión sobre los resultados obtenidos, que se centra en resaltar las ventajas, limitaciones y diferencias de los modelos propuestos, y de estos con respecto al estado del arte.
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Hernoux, Franck. "Conception et évaluation d'un système transparent de capture de mouvements des mains pour l'interaction 3D temps réel en environnements virtuels." Phd thesis, Ecole nationale supérieure d'arts et métiers - ENSAM, 2011. http://pastel.archives-ouvertes.fr/pastel-00651084.
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Le but de cette thèse est de proposer et d'évaluer un système transparent de capture de mouvements des mains en temps réel pour permettre la réalisation d'interactions 3D en environnement virtuel (E.V.). Les outils tels que le clavier et la souris ne suffisent plus lorsque l'on travaille dans des E.V. 3D et les systèmes de capture de mouvements actuels ont l'inconvénient du coût et du port de matériel. Les systèmes basés sur des caméras et le traitement d'images comblent en partie ces lacunes, mais ne permettent pas encore une capture de mouvements 3D précise, efficace et temps réel. Notre système propose une solution à ce problème grâce à une caméra 3D. Nous avons implémenté des modalités qui permettent une interaction plus naturelle avec les objets et l'E.V. L'objectif de notre système est d'obtenir des performances au moins égales à celles d'outils couramment utilisés en réalité virtuelle tout en offrant une meilleure acceptabilité globale, mesurée sous l'angle de l'utilité, de l'utilisabilité et du sentiment d'immersion. Pour répondre à cet objectif, nous avons mené 3 études expérimentales impliquant plus de 100 participants. L'étude 1 a comparé, pour une tâche de sélection, la première version de notre système (basé sur une Camera 3D MESA SwissRanger) à une souris classique. L'expérimentation 2 est axée sur l'étude de la réalisation de tâches de manipulation d'objets (positionnement, orientation, redimensionnement) et de navigation en E.V. Pour cette étude, nous avons comparé la version améliorée de notre système (basée sur la Microsoft Kinect) à des gants de données associés à des capteurs magnétiques. La 3ème étude, complémentaire, porte sur l'évaluation de nouvelles modalités d'interaction, implémentées d'après les commentaires recueillis auprès des participants de la seconde étude.
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Lagarde, Matthieu, Philippe Gaussier, and Pierre Andry. "Apprentissage de nouveaux comportements: vers le développement épigénétique d'un robot autonome." Phd thesis, Université de Cergy Pontoise, 2010. http://tel.archives-ouvertes.fr/tel-00749761.
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La problématique de l'apprentissage de comportements sur un robot autonome soulève de nombreuses questions liées au contrôle moteur, à l'encodage du comportement, aux stratégies comportementales et à la sélection de l'action. Utiliser une approche développementale présente un intérêt tout particulier dans le cadre de la robotique autonome. Le comportement du robot repose sur des mécanismes de bas niveau dont les interactions permettent de faire émerger des comportements plus complexes. Le robot ne possède pas d'informations a priori sur ses caractéristiques physiques ou sur l'environnement, il doit apprendre sa propre dynamique sensori-motrice. J'ai débuté ma thèse par l'étude d'un modèle d'imitation bas niveau. Du point de vue du développement, l'imitation est présente dès la naissance et accompagne, sous de multiples formes, le développement du jeune enfant. Elle présente une fonction d'apprentissage et se révèle alors être un atout en terme de temps d'acquisition de comportements, ainsi qu'une fonction de communication participant à l'amorce et au maintien d'interactions non verbales et naturelles. De plus, même s'il n'y a pas de réelle intention d'imiter, l'observation d'un autre agent permet d'extraire suffisamment d'informations pour être capable de reproduire la tâche. Mon travail a donc dans un premier temps consisté à appliquer et tester un modèle développemental qui permet l'émergence de comportements d'imitation de bas niveau sur un robot autonome. Ce modèle est construit comme un homéostat qui tend à équilibrer par l'action ses informations perceptives frustres (détection du mouvement, détection de couleur, informations sur les angles des articulations d'un bras de robot). Ainsi, lorsqu'un humain bouge sa main dans le champ visuel du robot, l'ambigüité de la perception de ce dernier lui fait confondre la main de l'humain avec l'extrémité de son bras. De l'erreur qui en résulte émerge un comportement d'imitation immédiate des gestes de l'humain par action de l'homéostat. Bien sûr, un tel modèle implique que le robot soit capable d'associer au préalable les positions visuelles de son effecteur avec les informations proprioceptives de ses moteurs. Grace au comportement d'imitation, le robot réalise des mouvements qu'il peut ensuite apprendre pour construire des comportements plus complexes. Comment alors passer d'un simple mouvement à un geste plus complexe pouvant impliquer un objet ou un lieu ? Je propose une architecture qui permet à un robot d'apprendre un comportement sous forme de séquences temporelles complexes (avec répétition d'éléments) de mouvements. Deux modèles différents permettant l'apprentissage de séquences ont été développés et testés. Le premier apprend en ligne le timing de séquences temporelles simples. Ce modèle ne permettant pas d'apprendre des séquences complexes, le second modèle testé repose sur les propriétés d'un réservoir de dynamiques, il apprend en ligne des séquences complexes. A l'issue de ces travaux, une architecture apprenant le timing d'une séquence complexe a été proposée. Les tests en simulation et sur robot ont montré la nécessité d'ajouter un mécanisme de resynchronisation permettant de retrouver les bons états cachés pour permettre d'amorcer une séquence complexe par un état intermédiaire. Dans un troisième temps, mes travaux ont consisté à étudier comment deux stratégies sensorimotrices peuvent cohabiter dans le cadre d'une tâche de navigation. La première stratégie encode le comportement à partir d'informations spatiales alors que la seconde utilise des informations temporelles. Les deux architectures ont été testées indépendamment sur une même tâche. Ces deux stratégies ont ensuite été fusionnées et exécutées en parallèle. La fusion des réponses délivrées par les deux stratégies a été réalisée avec l'utilisation de champs de neurones dynamiques. Un mécanisme de "chunking" représentant l'état instantané du robot (le lieu courant avec l'action courante) permet de resynchroniser les dynamiques des séquences temporelles. En parallèle, un certain nombre de problème de programmation et de conception des réseaux de neurones sont apparus. En effet, nos réseaux peuvent compter plusieurs centaines de milliers de neurones. Il devient alors difficile de les exécuter sur une seule unité de calcul. Comment concevoir des architectures neuronales avec des contraintes de répartition de calcul, de communications réseau et de temps réel ? Une autre partie de mon travail a consisté à apporter des outils permettant la modélisation, la communication et l'exécution en temps réel d'architecture distribuées. Pour finir, dans le cadre du projet européen Feelix Growing, j'ai également participé à l'intégration de mes travaux avec ceux du laboratoire LASA de l'EPFL pour l'apprentissage de comportements complexes mêlant la navigation, le geste et l'objet. En conclusion, cette thèse m'a permis de développer à la fois de nouveaux modèles pour l'apprentissage de comportements - dans le temps et dans l'espace, de nouveaux outils pour maîtriser des réseaux de neurones de très grande taille et de discuter à travers les limitations du système actuel, les éléments importants pour un système de sélection de l'action.
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Aganj, Ehsan. "Multi-view Reconstruction and Texturing=Reconstruction multi-vues et texturation." Phd thesis, Ecole des Ponts ParisTech, 2009. http://pastel.archives-ouvertes.fr/pastel-00517742.
Full textAbstract:
Dans cette thèse, nous étudions les problèmes de reconstruction statique et dynamique à partir de vues multiples et texturation, en s'appuyant sur des applications réelles et pratiques. Nous proposons trois méthodes de reconstruction destinées à l'estimation d'une représentation d'une scène statique/dynamique à partir d'un ensemble d'images/vidéos. Nous considérons ensuite le problème de texturation multi-vues en se concentrant sur la qualité visuelle de rendu..
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Guillaumin, Matthieu. "Données multimodales pour l'analyse d'image." Phd thesis, Grenoble, 2010. http://tel.archives-ouvertes.fr/tel-00522278/en/.
Full textAbstract:
La présente thèse s'intéresse à l'utilisation de méta-données textuelles pour l'analyse d'image. Nous cherchons à utiliser ces informations additionelles comme supervision faible pour l'apprentissage de modèles de reconnaissance visuelle. Nous avons observé un récent et grandissant intérêt pour les méthodes capables d'exploiter ce type de données car celles-ci peuvent potentiellement supprimer le besoin d'annotations manuelles, qui sont coûteuses en temps et en ressources. Nous concentrons nos efforts sur deux types de données visuelles associées à des informations textuelles. Tout d'abord, nous utilisons des images de dépêches qui sont accompagnées de légendes descriptives pour s'attaquer à plusieurs problèmes liés à la reconnaissance de visages. Parmi ces problèmes, la vérification de visages est la tâche consistant à décider si deux images représentent la même personne, et le nommage de visages cherche à associer les visages d'une base de données à leur noms corrects. Ensuite, nous explorons des modèles pour prédire automatiquement les labels pertinents pour des images, un problème connu sous le nom d'annotation automatique d'image. Ces modèles peuvent aussi être utilisés pour effectuer des recherches d'images à partir de mots-clés. Nous étudions enfin un scénario d'apprentissage multimodal semi-supervisé pour la catégorisation d'image. Dans ce cadre de travail, les labels sont supposés présents pour les données d'apprentissage, qu'elles soient manuellement annotées ou non, et absentes des données de test. Nos travaux se basent sur l'observation que la plupart de ces problèmes peuvent être résolus si des mesures de similarité parfaitement adaptées sont utilisées. Nous proposons donc de nouvelles approches qui combinent apprentissage de distance, modèles par plus proches voisins et méthodes par graphes pour apprendre, à partir de données visuelles et textuelles, des similarités visuelles spécifiques à chaque problème. Dans le cas des visages, nos similarités se concentrent sur l'identité des individus tandis que, pour les images, elles concernent des concepts sémantiques plus généraux. Expérimentalement, nos approches obtiennent des performances à l'état de l'art sur plusieurs bases de données complexes. Pour les deux types de données considérés, nous montrons clairement que l'apprentissage bénéficie de l'information textuelle supplémentaire résultant en l'amélioration de la performance des systèmes de reconnaissance visuelle.
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Wolf, Rémi. "Quantification de la qualité d'un geste chirurgical à partir de connaissances a priori." Phd thesis, Université de Grenoble, 2013. http://tel.archives-ouvertes.fr/tel-00965163.
Full textAbstract:
Le développement de la chirurgie laparoscopique entraîne de nouveaux défis pour le chirurgien, sa perception visuelle et tactile du site opératoire étant modifiée par rapport à son expérience antérieure. De nombreux dispositifs ont été développés autour de la procédure chirurgicale afin d'aider le chirurgien à réaliser le geste avec la meilleure qualité possible. Ces dispositifs visent à permettre au chirurgien de mieux percevoir le contexte dans lequel il intervient, à planifier de façon optimale la stratégie opératoire et à l'assister lors de la réalisation de son geste. La conception d'un système d'analyse de la procédure chirurgicale, permettant d'identifier des situations à risque et d'améliorer la qualité du geste, est un enjeu majeur du domaine des Gestes Médico-Chirurgicaux Assistés par Ordinateur. L'évaluation de la qualité du geste explore plusieurs composantes de sa réalisation : les habiletés techniques du chirurgien, ainsi que ses connaissances théoriques et sa capacité de jugement. L'objectif de cette thèse était de développer une méthode d'évaluation de la qualité technique des gestes du chirurgien à partir de connaissances à priori, qui soit adaptée aux contraintes spécifiques du bloc opératoire sans modifier l'environnement du chirurgien. Cette évaluation s'appuie sur la définition de métriques prédictives de la qualité du geste chirurgical, dérivées des trajectoires des instruments au cours de la procédure. La première étape de ce travail a donc consisté en la mise au point d'une méthode de suivi de la position des instruments laparoscopiques dans la cavité abdominale au cours de la chirurgie, à partir des images endoscopiques et sans ajout de marqueurs. Ce suivi combine des modèles géométriques de la caméra, de l'instrument et de son orientation, ainsi que des modèles statistiques décrivant les évolutions de cette dernière. Cette méthode permet le suivi de plusieurs instruments de laparoscopie dans des conditions de banc d'entraînement, en temps différé pour le moment. La seconde étape a consisté à extraire des trajectoires des paramètres prédictifs de la qualité du geste chirurgical, à partir de régressions aux moindres carrés partiels et de classifieurs k-means. Plusieurs nouvelles métriques ont été identifiées, se rapportant à la coordination des mains du chirurgien ainsi qu'à l'optimisation de son espace de travail. Ce dispositif est destiné à s'intégrer dans un système plus large, permettant d'apporter au chirurgien, en temps réel, des informations contextualisées concernant son geste, en fusionnant par exemple les données issues de la trajectoire à des données multi-modales d'imagerie per-opératoire.
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Baccouche, Moez. "Apprentissage neuronal de caractéristiques spatio-temporelles pour la classification automatique de séquences vidéo." Phd thesis, INSA de Lyon, 2013. http://tel.archives-ouvertes.fr/tel-00932662.
Full textAbstract:
Cette thèse s'intéresse à la problématique de la classification automatique des séquences vidéo. L'idée est de se démarquer de la méthodologie dominante qui se base sur l'utilisation de caractéristiques conçues manuellement, et de proposer des modèles qui soient les plus génériques possibles et indépendants du domaine. Ceci est fait en automatisant la phase d'extraction des caractéristiques, qui sont dans notre cas générées par apprentissage à partir d'exemples, sans aucune connaissance a priori. Nous nous appuyons pour ce faire sur des travaux existants sur les modèles neuronaux pour la reconnaissance d'objets dans les images fixes, et nous étudions leur extension au cas de la vidéo. Plus concrètement, nous proposons deux modèles d'apprentissage des caractéristiques spatio-temporelles pour la classification vidéo : (i) Un modèle d'apprentissage supervisé profond, qui peut être vu comme une extension des modèles ConvNets au cas de la vidéo, et (ii) Un modèle d'apprentissage non supervisé, qui se base sur un schéma d'auto-encodage, et sur une représentation parcimonieuse sur-complète des données. Outre les originalités liées à chacune de ces deux approches, une contribution supplémentaire de cette thèse est une étude comparative entre plusieurs modèles de classification de séquences parmi les plus populaires de l'état de l'art. Cette étude a été réalisée en se basant sur des caractéristiques manuelles adaptées à la problématique de la reconnaissance d'actions dans les vidéos de football. Ceci a permis d'identifier le modèle de classification le plus performant (un réseau de neurone récurrent bidirectionnel à longue mémoire à court-terme -BLSTM-), et de justifier son utilisation pour le reste des expérimentations. Enfin, afin de valider la généricité des deux modèles proposés, ceux-ci ont été évalués sur deux problématiques différentes, à savoir la reconnaissance d'actions humaines (sur la base KTH), et la reconnaissance d'expressions faciales (sur la base GEMEP-FERA). L'étude des résultats a permis de valider les approches, et de montrer qu'elles obtiennent des performances parmi les meilleures de l'état de l'art (avec 95,83% de bonne reconnaissance pour la base KTH, et 87,57% pour la base GEMEP-FERA).
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"Learning-based descriptor for 2-D face recognition." 2010. http://library.cuhk.edu.hk/record=b5894302.
Full textAbstract:
Cao, Zhimin.Thesis (M.Phil.)--Chinese University of Hong Kong, 2010.
Includes bibliographical references (leaves 30-34).
Abstracts in English and Chinese.
Chapter 1 --- Introduction and related work --- p.1
Chapter 2 --- Learning-based descriptor for face recognition --- p.7
Chapter 2.1 --- Overview of framework --- p.7
Chapter 2.2 --- Learning-based descriptor extraction --- p.9
Chapter 2.2.1 --- Sampling and normalization --- p.9
Chapter 2.2.2 --- Learning-based encoding and histogram rep-resentation --- p.11
Chapter 2.2.3 --- PCA dimension reduction --- p.12
Chapter 2.2.4 --- Multiple LE descriptors --- p.14
Chapter 2.3 --- Pose-adaptive matching --- p.16
Chapter 2.3.1 --- Component -level face alignment --- p.17
Chapter 2.3.2 --- Pose-adaptive matching --- p.17
Chapter 2.3.3 --- Evaluations of pose-adaptive matching --- p.19
Chapter 3 --- Experiment --- p.21
Chapter 3.1 --- Results on the LFW benchmark --- p.21
Chapter 3.2 --- Results on Multi-PIE --- p.24
Chapter 4 --- Conclusion and future work --- p.27
Chapter 4.1 --- Conclusion --- p.27
Chapter 4.2 --- Future work --- p.28
Bibliography --- p.30
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"Symmetry for face analysis." 2005. http://library.cuhk.edu.hk/record=b5892640.
Full textAbstract:
Yuan Tianqiang.Thesis (M.Phil.)--Chinese University of Hong Kong, 2005.
Includes bibliographical references (leaves 51-55).
Abstracts in English and Chinese.
abstract --- p.i
acknowledgments --- p.iv
table of contents --- p.v
list of figures --- p.vii
list of tables --- p.ix
Chapter Chapter 1 --- Introduction --- p.1
Chapter 1.1 --- Reflectional Symmetry Detection --- p.1
Chapter 1.2 --- Research Progress on Face Analysis --- p.2
Chapter 1.2.1 --- Face Detection --- p.3
Chapter 1.2.2 --- Face Alignment --- p.4
Chapter 1.2.3 --- Face Recognition --- p.6
Chapter 1.3 --- Organization of this thesis --- p.8
Chapter Chapter 2 --- Local reflectional symmetry detection --- p.9
Chapter 2.1 --- Proposed Method --- p.9
Chapter 2.1.1 --- Symmetry measurement operator --- p.9
Chapter 2.1.2 --- Potential regions selection --- p.10
Chapter 2.1.3 --- Detection of symmetry axes --- p.11
Chapter 2.2 --- Experiments --- p.13
Chapter 2.2.1 --- Parameter setting and analysis --- p.13
Chapter 2.2.2 --- Experimental Results --- p.14
Chapter Chapter 3 --- Global perspective reflectional symmetry detection --- p.16
Chapter 3.1 --- Introduction of camera models --- p.16
Chapter 3.2 --- Property of Symmetric Point-Pair --- p.18
Chapter 3.3 --- analysis and Experiment --- p.20
Chapter 3.3.1 --- Confirmative Experiments --- p.20
Chapter 3.3.2 --- Face shape generation with PSI --- p.22
Chapter 3.3.3 --- Error Analysis --- p.24
Chapter 3.3.4 --- Experiments of Pose Estimation --- p.25
Chapter 3.4 --- Summary --- p.28
Chapter Chapter 4 --- Pre-processing of face analysis --- p.30
Chapter 4.1 --- Introduction of Hough Transform --- p.30
Chapter 4.2 --- Eye Detection --- p.31
Chapter 4.2.1 --- Coarse Detection --- p.32
Chapter 4.2.2 --- Refine the eyes positions --- p.34
Chapter 4.2.3 --- Experiments and Analysis --- p.35
Chapter 4.3 --- Face Components Detection with GHT --- p.37
Chapter 4.3.1 --- Parameter Analyses --- p.38
Chapter 4 3.2 --- R-table Construction --- p.38
Chapter 4.3.3 --- Detection Procedure and Voting Strategy --- p.39
Chapter 4.3.4 --- Experiments and Analysis --- p.41
Chapter Chapter 5 --- Pose estimation with face symmetry --- p.45
Chapter 5.1 --- Key points selection --- p.45
Chapter 5.2 --- Face Pose Estimation --- p.46
Chapter 5.2.1 --- Locating eye corners --- p.46
Chapter 5.2.2 --- Analysis and Summary --- p.47
Chapter Chapter 6 --- Conclusions and future work --- p.49
bibliography --- p.51
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"Rotation-invariant face detection in grayscale images." 2005. http://library.cuhk.edu.hk/record=b5892397.
Full textAbstract:
Zhang Wei.Thesis (M.Phil.)--Chinese University of Hong Kong, 2005.
Includes bibliographical references (leaves 73-78).
Abstracts in English and Chinese.
Abstract --- p.i
Acknowledgement --- p.ii
List of Figures --- p.viii
List of Tables --- p.ix
Chapter 1 --- Introduction --- p.1
Chapter 1.1 --- Previous work --- p.2
Chapter 1.1.1 --- Learning-based approaches --- p.3
Chapter 1.1.2 --- Feature-based approaches --- p.7
Chapter 1.2 --- Thesis objective --- p.12
Chapter 1.3 --- The proposed detector --- p.13
Chapter 1.4 --- Thesis outline --- p.14
Chapter 2 --- The Edge Merging Algorithm --- p.16
Chapter 2.1 --- Edge detection --- p.16
Chapter 2.2 --- Edge breaking --- p.18
Chapter 2.2.1 --- Cross detection --- p.20
Chapter 2.2.2 --- Corner detection --- p.20
Chapter 2.3 --- Curve merging --- p.23
Chapter 2.3.1 --- The search region --- p.25
Chapter 2.3.2 --- The merging cost function --- p.27
Chapter 2.4 --- Ellipse fitting --- p.30
Chapter 2.5 --- Discussion --- p.33
Chapter 3 --- The Face Verifier --- p.35
Chapter 3.1 --- The face box --- p.35
Chapter 3.1.1 --- Face box localization --- p.36
Chapter 3.1.2 --- Conditioning the face box --- p.42
Chapter 3.2 --- Eye-mouth triangle search --- p.45
Chapter 3.3 --- Face model matching --- p.48
Chapter 3.3.1 --- Face model construction --- p.48
Chapter 3.3.2 --- Confidence of detection --- p.51
Chapter 3.4 --- Dealing with overlapped detections --- p.51
Chapter 3.5 --- Discussion --- p.53
Chapter 4 --- Experiments --- p.55
Chapter 4.1 --- The test sets --- p.55
Chapter 4.2 --- Experimental results --- p.56
Chapter 4.2.1 --- The ROC curves --- p.56
Chapter 4.3 --- Discussions --- p.61
Chapter 5 --- Conclusions --- p.69
Chapter 5.1 --- Conclusions --- p.69
Chapter 5.2 --- Suggestions for future work --- p.70
List of Original Contributions --- p.72
Bibliography --- p.73
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McLindin, Brett Alan. "Improving the performance of two dimensional facial recognition systems the development of a generic model for biometric technology variables in operational environments." 2005. http://arrow.unisa.edu.au:8081/1959.8/25036.
Full textAbstract:
In recent times, there has been an increase in national security awareness with a focus on improving current practices relating to the identification and verification of individuals and the reduction of identity fraud. One tool that has been found to assist in these areas is biometrics. This thesis examines some biometric technologies that may be potentially suitable for surveillance and access control applications, and shows why facial recognition technology has been the focus of this study. Despite the testing reported in the literature discussing attempts to solve the problems with facial recognition operational performance, facial recognition has not been widely implemented in security applications to date. The reported testing regimes vary in terms of the date of testing, methodology used for the study, evaluation type, test size and the extent to which possible variations of each variable were examined. To summarise what is known about the effect each variable has on performance, a baseline model of variables together with a ranking scheme is defined and utilised to create a starting point for the research. The research described in this thesis focuses on how to improve the operational performance of two dimensional facial recognition systems by building upon the baseline model of variables and by better understanding how the variables affect facial recognition performance. To improve on the baseline model, systems engineering techniques are used to identify the functional components of a generic facial recognition system, the relationships between them, and the variables that affect those relationships. This identifies other variables that may affect performance. In order to determine which variables affect performance, and how, a series of technical, scenario and operational experiments are conducted to test a selection of the variables. It is shown that this results in a greater understanding of how facial recognition systems react to different variables in operational environments. A revised model of ranked variables is produced that can then be used by current and prospective stakeholders of biometric systems, system designers, integrators and testers to ensure that the majority of the variables are considered when designing, installing, commissioning, or testing facial recognition systems. The findings of this research can also be used to critically analyse existing facial recognition system implementations in order to identify areas where performance increases are possible. This is confirmed in part throughout the two year testing phase of this research where data collected from initial experiments were used as a starting point to improve the performance of later operational experiments. Finally, this thesis identifies that the revised model of variables is sufficiently generic to be used as a starting point for analysing a system using any biometric technology. This is supported by using iris recognition technology as a test case. It is anticipated that with an increased knowledge of how some systems are affected by certain variables, and by better controlling those variables, an increase in performance is possible for access control and surveillance security applications that utilise biometric technologies.thesis (PhDElectronicSystemsEngineering)--University of South Australia, 2005.
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Van, der Schyff Marco. "Bandwidth efficient virtual classroom." Thesis, 2009. http://hdl.handle.net/10210/2186.
Full textAbstract:
M.Ing.Virtual classrooms and online-learning are growing in popularity, but there are still some factors limiting the potential. Limited bandwidth for audio and video, the resultant transmission quality and limited feedback during virtual classroom sessions are some of the problems that need to be addressed. This thesis presents information on the design and implementation of various components of a virtual classroom system for researching methods of student feedback with a focus on bandwidth conservation. A facial feature technique is implemented and used within the system to determine the viability of using facial feature extraction to provide and prioritise feedback from students to teacher while conserving bandwidth. This allows a teacher to estimate the comprehension level of the class and individual students based on student images. A server determines which student terminal transmits its images to the teacher using data obtained from the facial feature extraction process. Feedback is improved as teachers adapt to class circumstances using experience gained in traditional classrooms. Feedback is also less reliant on intentional student participation. New page-turner, page suggestion and class activity components are presented as possible methods for improving student feedback. In particular, the effect of virtual classroom system parameters on feedback delays and bandwidth usage is investigated. In general, delays are increased as bandwidth requirements decrease. The system shows promise for future use in research on facial feature extraction, student feedback and bandwidth conservation in virtual classrooms.
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"3D object retrieval and recognition." 2010. http://library.cuhk.edu.hk/record=b5894304.
Full textAbstract:
Gong, Boqing.Thesis (M.Phil.)--Chinese University of Hong Kong, 2010.
Includes bibliographical references (p. 53-59).
Abstracts in English and Chinese.
Chapter 1 --- Introduction --- p.1
Chapter 1.1 --- 3D Object Representation --- p.1
Chapter 1.1.1 --- Polygon Mesh --- p.2
Chapter 1.1.2 --- Voxel --- p.2
Chapter 1.1.3 --- Range Image --- p.3
Chapter 1.2 --- Content-Based 3D Object Retrieval --- p.3
Chapter 1.3 --- 3D Facial Expression Recognition --- p.4
Chapter 1.4 --- Contributions --- p.5
Chapter 2 --- 3D Object Retrieval --- p.6
Chapter 2.1 --- A Conceptual Framework for 3D Object Retrieval --- p.6
Chapter 2.1.1 --- Query Formulation and User Interface --- p.7
Chapter 2.1.2 --- Canonical Coordinate Normalization --- p.8
Chapter 2.1.3 --- Representations of 3D Objects --- p.10
Chapter 2.1.4 --- Performance Evaluation --- p.11
Chapter 2.2 --- Public Databases --- p.13
Chapter 2.2.1 --- Databases of Generic 3D Objects --- p.14
Chapter 2.2.2 --- A Database of Articulated Objects --- p.15
Chapter 2.2.3 --- Domain-Specific Databases --- p.15
Chapter 2.2.4 --- Data Sets for the Shrec Contest --- p.16
Chapter 2.3 --- Experimental Systems --- p.16
Chapter 2.4 --- Challenges in 3D Object Retrieval --- p.17
Chapter 3 --- Boosting 3D Object Retrieval by Object Flexibility --- p.19
Chapter 3.1 --- Related Work --- p.19
Chapter 3.2 --- Object Flexibility --- p.21
Chapter 3.2.1 --- Definition --- p.21
Chapter 3.2.2 --- Computation of the Flexibility --- p.22
Chapter 3.3 --- A Flexibility Descriptor for 3D Object Retrieval --- p.24
Chapter 3.4 --- Enhancing Existing Methods --- p.25
Chapter 3.5 --- Experiments --- p.26
Chapter 3.5.1 --- Retrieving Articulated Objects --- p.26
Chapter 3.5.2 --- Retrieving Generic Objects --- p.27
Chapter 3.5.3 --- Experiments on Larger Databases --- p.28
Chapter 3.5.4 --- Comparison of Times for Feature Extraction --- p.31
Chapter 3.6 --- Conclusions & Analysis --- p.31
Chapter 4 --- 3D Object Retrieval with Referent Objects --- p.32
Chapter 4.1 --- 3D Object Retrieval with Prior --- p.32
Chapter 4.2 --- 3D Object Retrieval with Referent Objects --- p.34
Chapter 4.2.1 --- Natural and Man-made 3D Object Classification --- p.35
Chapter 4.2.2 --- Inferring Priors Using 3D Object Classifier --- p.36
Chapter 4.2.3 --- Reducing False Positives --- p.37
Chapter 4.3 --- Conclusions and Future Work --- p.38
Chapter 5 --- 3D Facial Expression Recognition --- p.39
Chapter 5.1 --- Introduction --- p.39
Chapter 5.2 --- Separation of BFSC and ESC --- p.43
Chapter 5.2.1 --- 3D Face Alignment --- p.43
Chapter 5.2.2 --- Estimation of BFSC --- p.44
Chapter 5.3 --- Expressional Regions and an Expression Descriptor --- p.45
Chapter 5.4 --- Experiments --- p.47
Chapter 5.4.1 --- Testing the Ratio of Preserved Energy in the BFSC Estimation --- p.47
Chapter 5.4.2 --- Comparison with Related Work --- p.48
Chapter 5.5 --- Conclusions --- p.50
Chapter 6 --- Conclusions --- p.51
Bibliography --- p.53
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Denys, Nele. "Multimodal verification of identity for a realistic access control application." Thesis, 2008. http://hdl.handle.net/10210/1734.
Full textAbstract:
D. Ing.This thesis describes a real world application in the field of pattern recognition. License plate recognition and face recognition algorithms are combined to implement automated access control at the gates of RAU campus. One image of the license plate and three images of the driver’s face are enough to check if the person driving a particular car into campus is the same as the person driving this car out. The license plate recognition module is based on learning vector quantization and performs well enough to be used in a realistic environment. The face recognition module is based on the Bayes rule and while performing satisfactory, extensive research is still necessary before this system can be implemented in real life. The main reasons for failure of the system were identified as the variable lighting and insufficient landmarks for effective warping.
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Barczak, Andre Luis Chautard. "Feature-based rapid object detection : from feature extraction to parallelisation : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Computer Sciences at Massey University, Auckland, New Zealand." 2007. http://hdl.handle.net/10179/742.
Full textAbstract:
This thesis studies rapid object detection, focusing on feature-based methods. Firstly, modifications of training and detection of the Viola-Jones method are made to improve performance and overcome some of the current limitations such as rotation, occlusion and articulation. New classifiers produced by training and by converting existing classifiers are tested in face detection and hand detection. Secondly, the nature of invariant features in terms of the computational complexity, discrimination power and invariance to rotation and scaling are discussed. A new feature extraction method called Concentric Discs Moment Invariants (CDMI) is developed based on moment invariants and summed-area tables. The dimensionality of this set of features can be increased by using additional concentric discs, rather than using higher order moments. The CDMI set has useful properties, such as speed, rotation invariance, scaling invariance, and rapid contrast stretching can be easily implemented. The results of experiments with face detection shows a clear improvement in accuracy and performance of the CDMI method compared to the standard moment invariants method. Both the CDMI and its variant, using central moments from concentric squares, are used to assess the strength of the method applied to hand-written digits recognition. Finally, the parallelisation of the detection algorithm is discussed. A new model for the specific case of the Viola-Jones method is proposed and tested experimentally. This model takes advantage of the structure of classifiers and of the multi-resolution approach associated with the detection method. The model shows that high speedups can be achieved by broadcasting frames and carrying out the computation of one or more cascades in each node.
42
"Audio-guided video based face recognition." Thesis, 2006. http://library.cuhk.edu.hk/record=b6074161.
Full textAbstract:
Face recognition is one of the most challenging computer vision research topics since faces appear differently even for the same person due to expression, pose, lighting, occlusion and many other confounding factors in real life. During the past thirty years, a number of face recognition techniques have been proposed. However, all of these methods focus exclusively on image-based face recognition that uses a still image as input data. One problem with the image-based face recognition is that it is possible to use a pre-recorded face photo to confuse a camera to take it as a live subject. The second problem is that the image-based recognition accuracy is still too low in some practical applications comparing to other high accuracy biometric technologies. To alleviate these problems, video based face recognition has been proposed recently. One of the major advantages of video-based face recognition is to prevent the fraudulent system penetration by pre-recorded facial images. The great difficulty to forge a video sequence (possible but very difficult) in front of a live video camera may ensure that the biometric data come from the user at the time of authentication. Another key advantage of the video based method is that more information is available in a video sequence than in a single image. If the additional information can be properly extracted, we can further increase the recognition accuracy.In this thesis, we develop a new video-to-video face recognition algorithm [86]. The major advantage of the video based method is that more information is available in a video sequence than in a single image. In order to take advantage of the large amount of information in the video sequence and at the same time overcome the processing speed and data size problems we develop several new techniques including temporal and spatial frame synchronization, multi-level subspace analysis, and multi-classifier integration for video sequence processing. An aligned video sequence for each person is first obtained by applying temporal and spatial synchronization, which effectively establishes the face correspondence using the information of both audio and video, then multi-level subspace analysis or multi-classifier integration is employed for further analysis based on the synchronized sequence. The method preserves all the temporal-spatial information contained in a video sequence. Near perfect classification results are obtained on the largest available XM2VTS face video database. In addition, using a similar framework, two kinds of much improved still image based face recognition algorithms [93][94] are developed by incorporating the Gabor representation, nonparametric feature extraction method, and multiple classifier integration techniques. Extensive experiments on two famous face databases (XM2VTS database and Purdue database) clearly show the superiority of our new algorithms.
by Li Zhifeng.
"March 2006."
Adviser: Xiaoou Tang.
Source: Dissertation Abstracts International, Volume: 67-11, Section: B, page: 6621.
Thesis (Ph.D.)--Chinese University of Hong Kong, 2006.
Includes bibliographical references (p. 105-114).
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Abstracts in English and Chinese.
School code: 1307.
43
"A generic face processing framework: technologies, analyses and applications." 2003. http://library.cuhk.edu.hk/record=b5891585.
Full textAbstract:
Jang Kim-fung.Thesis (M.Phil.)--Chinese University of Hong Kong, 2003.
Includes bibliographical references (leaves 108-124).
Abstracts in English and Chinese.
Abstract --- p.i
Acknowledgement --- p.iii
Chapter 1 --- Introduction --- p.1
Chapter 1.1 --- Background --- p.1
Chapter 1.2 --- Introduction about Face Processing Framework --- p.4
Chapter 1.2.1 --- Basic architecture --- p.4
Chapter 1.2.2 --- Face detection --- p.5
Chapter 1.2.3 --- Face tracking --- p.6
Chapter 1.2.4 --- Face recognition --- p.6
Chapter 1.3 --- The scope and contributions of the thesis --- p.7
Chapter 1.4 --- The outline of the thesis --- p.8
Chapter 2 --- Facial Feature Representation --- p.10
Chapter 2.1 --- Facial feature analysis --- p.10
Chapter 2.1.1 --- Pixel information --- p.11
Chapter 2.1.2 --- Geometry information --- p.13
Chapter 2.2 --- Extracting and coding of facial feature --- p.14
Chapter 2.2.1 --- Face recognition --- p.15
Chapter 2.2.2 --- Facial expression classification --- p.38
Chapter 2.2.3 --- Other related work --- p.44
Chapter 2.3 --- Discussion about facial feature --- p.48
Chapter 2.3.1 --- Performance evaluation for face recognition --- p.49
Chapter 2.3.2 --- Evolution of the face recognition --- p.52
Chapter 2.3.3 --- Evaluation of two state-of-the-art face recog- nition methods --- p.53
Chapter 2.4 --- Problem for current situation --- p.58
Chapter 3 --- Face Detection Algorithms and Committee Ma- chine --- p.61
Chapter 3.1 --- Introduction about face detection --- p.62
Chapter 3.2 --- Face Detection Committee Machine --- p.64
Chapter 3.2.1 --- Review of three approaches for committee machine --- p.65
Chapter 3.2.2 --- The approach of FDCM --- p.68
Chapter 3.3 --- Evaluation --- p.70
Chapter 4 --- Facial Feature Localization --- p.73
Chapter 4.1 --- Algorithm for gray-scale image: template match- ing and separability filter --- p.73
Chapter 4.1.1 --- Position of face and eye region --- p.74
Chapter 4.1.2 --- Position of irises --- p.75
Chapter 4.1.3 --- Position of lip --- p.79
Chapter 4.2 --- Algorithm for color image: eyemap and separa- bility filter --- p.81
Chapter 4.2.1 --- Position of eye candidates --- p.81
Chapter 4.2.2 --- Position of mouth candidates --- p.83
Chapter 4.2.3 --- Selection of face candidates by cost function --- p.84
Chapter 4.3 --- Evaluation --- p.85
Chapter 4.3.1 --- Algorithm for gray-scale image --- p.86
Chapter 4.3.2 --- Algorithm for color image --- p.88
Chapter 5 --- Face Processing System --- p.92
Chapter 5.1 --- System architecture and limitations --- p.92
Chapter 5.2 --- Pre-processing module --- p.93
Chapter 5.2.1 --- Ellipse color model --- p.94
Chapter 5.3 --- Face detection module --- p.96
Chapter 5.3.1 --- Choosing the classifier --- p.96
Chapter 5.3.2 --- Verifying the candidate region --- p.97
Chapter 5.4 --- Face tracking module --- p.99
Chapter 5.4.1 --- Condensation algorithm --- p.99
Chapter 5.4.2 --- Tracking the region using Hue color model --- p.101
Chapter 5.5 --- Face recognition module --- p.102
Chapter 5.5.1 --- Normalization --- p.102
Chapter 5.5.2 --- Recognition --- p.103
Chapter 5.6 --- Applications --- p.104
Chapter 6 --- Conclusion --- p.106
Bibliography --- p.107
44
"Automatic segmentation and registration techniques for 3D face recognition." Thesis, 2008. http://library.cuhk.edu.hk/record=b6074674.
Full textAbstract:
A 3D range image acquired by 3D sensing can explicitly represent a three-dimensional object's shape regardless of the viewpoint and lighting variations. This technology has great potential to resolve the face recognition problem eventually. An automatic 3D face recognition system consists of three stages: facial region segmentation, registration and recognition. The success of each stage influences the system's ultimate decision. Lately, research efforts are mainly devoted to the last recognition stage in 3D face recognition research. In this thesis, our study mainly focuses on segmentation and registration techniques, with the aim of providing a more solid foundation for future 3D face recognition research.Then we propose a fully automatic registration method that can handle facial expressions with high accuracy and robustness for 3D face image alignment. In our method, the nose region, which is relatively more rigid than other facial regions in the anatomical sense, is automatically located and analyzed for computing the precise location of a symmetry plane. Extensive experiments have been conducted using the FRGC (V1.0 and V2.0) benchmark 3D face dataset to evaluate the accuracy and robustness of our registration method. Firstly, we compare its results with two other registration methods. One of these methods employs manually marked points on visualized face data and the other is based on the use of a symmetry plane analysis obtained from the whole face region. Secondly, we combine the registration method with other face recognition modules and apply them in both face identification and verification scenarios. Experimental results show that our approach performs better than the other two methods. For example, 97.55% Rank-1 identification rate and 2.25% EER score are obtained by using our method for registration and the PCA method for matching on the FRGC V1.0 dataset. All these results are the highest scores ever reported using the PCA method applied to similar datasets.
We firstly propose an automatic 3D face segmentation method. This method is based on deep understanding of 3D face image. Concepts of proportions of the facial and nose regions are acquired from anthropometrics for locating such regions. We evaluate this segmentation method on the FRGC dataset, and obtain a success rate as high as 98.87% on nose tip detection. Compared with results reported by other researchers in the literature, our method yields the highest score.
Tang, Xinmin.
Source: Dissertation Abstracts International, Volume: 70-06, Section: B, page: 3616.
Thesis (Ph.D.)--Chinese University of Hong Kong, 2008.
Includes bibliographical references (leaves 109-117).
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Abstracts in English and Chinese.
School code: 1307.
45
"Partial EBGM and face synthesis methods for non-frontal recognition." 2009. http://library.cuhk.edu.hk/record=b5894015.
Full textAbstract:
Cheung, Kin Wang.Thesis (M.Phil.)--Chinese University of Hong Kong, 2009.
Includes bibliographical references (leaves 76-82).
Abstract also in Chinese.
Chapter 1. --- INTRODUCTION --- p.1
Chapter 1.1. --- Background --- p.1
Chapter 1.1.1. --- Introduction to Biometrics --- p.1
Chapter 1.1.2. --- Face Recognition in General --- p.2
Chapter 1.1.3. --- A Typical Face Recognition System Architecture --- p.4
Chapter 1.1.4. --- Face Recognition in Surveillance Cameras --- p.6
Chapter 1.1.5. --- Face recognition under Pose Variation --- p.9
Chapter 1.2. --- Motivation and Objectives --- p.11
Chapter 1.3. --- Related Works --- p.13
Chapter 1.3.1. --- Overview of Pose-invariant Face Recognition --- p.13
Chapter 1.3.2. --- Standard Face Recognition Setting --- p.14
Chapter 1.3.3. --- Multi-Probe Setting --- p.19
Chapter 1.3.4. --- Multi-Gallery Setting --- p.21
Chapter 1.3.5. --- Non-frontal Face Databases --- p.23
Chapter 1.3.6. --- Evaluation Metrics --- p.26
Chapter 1.3.7. --- Summary of Non-frontal Face Recognition Settings --- p.27
Chapter 1.4. --- Proposed Methods for Non-frontal Face Recognition --- p.28
Chapter 1.5. --- Thesis Organization --- p.30
Chapter 2. --- PARTIAL ELASTIC BUNCH GRAPH MATCHING --- p.31
Chapter 2.1. --- Introduction --- p.31
Chapter 2.2. --- EBGM for Non-frontal Face Recognition --- p.31
Chapter 2.2.1. --- Overview of Baseline EBGM Algorithm --- p.31
Chapter 2.2.2. --- Modified EBGM for Non-frontal Face Matching --- p.33
Chapter 2.3. --- Experiments --- p.35
Chapter 2.3.1. --- Experimental Setup --- p.35
Chapter 2.3.2. --- Experimental Results --- p.37
Chapter 2.4. --- Discussions --- p.40
Chapter 3. --- FACE RECOGNITION BY FRONTAL VIEW SYNTHESIS WITH CALIBRATED STEREO CAMERAS --- p.43
Chapter 3.1. --- Introduction --- p.43
Chapter 3.2. --- Proposed Method --- p.44
Chapter 3.2.1. --- Image Rectification --- p.45
Chapter 3.2.2. --- Face Detection --- p.49
Chapter 3.2.3. --- Head Pose Estimation --- p.51
Chapter 3.2.4. --- Virtual View Generation --- p.52
Chapter 3.2.5. --- Feature Localization --- p.54
Chapter 3.2.6. --- Face Morphing --- p.56
Chapter 3.3. --- Experiments --- p.58
Chapter 3.3.1. --- Data Collection --- p.58
Chapter 3.3.2. --- Synthesized Results --- p.59
Chapter 3.3.3. --- Experiment Setup --- p.60
Chapter 3.3.4. --- Experiment Results on FERET database --- p.61
Chapter 3.3.5. --- Experiment Results on CAS-PEAL-R1 database --- p.62
Chapter 3.4. --- Discussions --- p.64
Chapter 3.5. --- Summary --- p.66
Chapter 4. --- "EXPERIMENTS, RESULTS AND OBSERVATIONS" --- p.67
Chapter 4.1. --- Experiment Setup --- p.67
Chapter 4.2. --- Experiment Results --- p.69
Chapter 4.3. --- Discussions --- p.70
Chapter 5. --- CONCLUSIONS --- p.74
Chapter 6. --- BIBLIOGRAPHY --- p.76
46
Song, Qing. "Features and statistical classifiers for face image analysis /." 2001.
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"Intensity based methodologies for facial expression recognition." 2001. http://library.cuhk.edu.hk/record=b5890656.
Full textAbstract:
by Hok Chun Lo.Thesis (M.Phil.)--Chinese University of Hong Kong, 2001.
Includes bibliographical references (leaves 136-143).
Abstracts in English and Chinese.
LIST OF FIGURES --- p.viii
LIST OF TABLES --- p.x
Chapter 1. --- INTRODUCTION --- p.1
Chapter 2. --- PREVIOUS WORK ON FACIAL EXPRESSION RECOGNITION --- p.9
Chapter 2.1. --- Active Deformable Contour --- p.9
Chapter 2.2. --- Facial Feature Points and B-spline Curve --- p.10
Chapter 2.3. --- Optical Flow Approach --- p.11
Chapter 2.4. --- Facial Action Coding System --- p.12
Chapter 2.5. --- Neural Network --- p.13
Chapter 3. --- EIGEN-ANALYSIS BASED METHOD FOR FACIAL EXPRESSION RECOGNITION --- p.15
Chapter 3.1. --- Related Topics on Eigen-Analysis Based Method --- p.15
Chapter 3.1.1. --- Terminologies --- p.15
Chapter 3.1.2. --- Principal Component Analysis --- p.17
Chapter 3.1.3. --- Significance of Principal Component Analysis --- p.18
Chapter 3.1.4. --- Graphical Presentation of the Idea of Principal Component Analysis --- p.20
Chapter 3.2. --- EigenFace Method for Face Recognition --- p.21
Chapter 3.3. --- Eigen-Analysis Based Method for Facial Expression Recognition --- p.23
Chapter 3.3.1. --- Person-Dependent Database --- p.23
Chapter 3.3.2. --- Direct Adoption of EigenFace Method --- p.24
Chapter 3.3.3. --- Multiple Subspaces Method --- p.27
Chapter 3.4. --- Detail Description on Our Approaches --- p.29
Chapter 3.4.1. --- Database Formation --- p.29
Chapter a. --- Conversion of Image to Column Vector --- p.29
Chapter b. --- "Preprocess: Scale Regulation, Orientation Regulation and Cropping." --- p.30
Chapter c. --- Scale Regulation --- p.31
Chapter d. --- Orientation Regulation --- p.32
Chapter e. --- Cropping of images --- p.33
Chapter f. --- Calculation of Expression Subspace for Direct Adoption Method --- p.35
Chapter g. --- Calculation of Expression Subspace for Multiple Subspaces Method. --- p.38
Chapter 3.4.2. --- Recognition Process for Direct Adoption Method --- p.38
Chapter 3.4.3. --- Recognition Process for Multiple Subspaces Method --- p.39
Chapter a. --- Intensity Normalization Algorithm --- p.39
Chapter b. --- Matching --- p.44
Chapter 3.5. --- Experimental Result and Analysis --- p.45
Chapter 4. --- DEFORMABLE TEMPLATE MATCHING SCHEME FOR FACIAL EXPRESSION RECOGNITION --- p.53
Chapter 4.1. --- Background Knowledge --- p.53
Chapter 4.1.1. --- Camera Model --- p.53
Chapter a. --- Pinhole Camera Model and Perspective Projection --- p.54
Chapter b. --- Orthographic Camera Model --- p.56
Chapter c. --- Affine Camera Model --- p.57
Chapter 4.1.2. --- View Synthesis --- p.58
Chapter a. --- Technique Issue of View Synthesis --- p.59
Chapter 4.2. --- View Synthesis Technique for Facial Expression Recognition --- p.68
Chapter 4.2.1. --- From View Synthesis Technique to Template Deformation --- p.69
Chapter 4.3. --- Database Formation --- p.71
Chapter 4.3.1. --- Person-Dependent Database --- p.72
Chapter 4.3.2. --- Model Images Acquisition --- p.72
Chapter 4.3.3. --- Templates' Structure and Formation Process --- p.73
Chapter 4.3.4. --- Selection of Warping Points and Template Anchor Points --- p.77
Chapter a. --- Selection of Warping Points --- p.78
Chapter b. --- Selection of Template Anchor Points --- p.80
Chapter 4.4. --- Recognition Process --- p.81
Chapter 4.4.1. --- Solving Warping Equation --- p.83
Chapter 4.4.2. --- Template Deformation --- p.83
Chapter 4.4.3. --- Template from Input Images --- p.86
Chapter 4.4.4. --- Matching --- p.87
Chapter 4.5. --- Implementation of Automation System --- p.88
Chapter 4.5.1. --- Kalman Filter --- p.89
Chapter 4.5.2. --- Using Kalman Filter for Trakcing in Our System --- p.89
Chapter 4.5.3. --- Limitation --- p.92
Chapter 4.6. --- Experimental Result and Analysis --- p.93
Chapter 5. --- CONCLUSION AND FUTURE WORK --- p.97
APPENDIX --- p.100
Chapter I. --- Image Sample 1 --- p.100
Chapter II. --- Image Sample 2 --- p.109
Chapter III. --- Image Sample 3 --- p.119
Chapter IV. --- Image Sample 4 --- p.135
BIBLIOGRAPHY --- p.136
48
Lee, Chan-Su. "Modeling human motion using manifold learning and factorized generative models." 2007. http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.13479.
Full text
49
"Face authentication on mobile devices: optimization techniques and applications." 2005. http://library.cuhk.edu.hk/record=b5892581.
Full textAbstract:
Pun Kwok Ho.Thesis (M.Phil.)--Chinese University of Hong Kong, 2005.
Includes bibliographical references (leaves 106-111).
Abstracts in English and Chinese.
Chapter 1. --- Introduction --- p.1
Chapter 1.1 --- Background --- p.1
Chapter 1.1.1 --- Introduction to Biometrics --- p.1
Chapter 1.1.2 --- Face Recognition in General --- p.2
Chapter 1.1.3 --- Typical Face Recognition Systems --- p.4
Chapter 1.1.4 --- Face Database and Evaluation Protocol --- p.5
Chapter 1.1.5 --- Evaluation Metrics --- p.7
Chapter 1.1.6 --- Characteristics of Mobile Devices --- p.10
Chapter 1.2 --- Motivation and Objectives --- p.12
Chapter 1.3 --- Major Contributions --- p.13
Chapter 1.3.1 --- Optimization Framework --- p.13
Chapter 1.3.2 --- Real Time Principal Component Analysis --- p.14
Chapter 1.3.3 --- Real Time Elastic Bunch Graph Matching --- p.14
Chapter 1.4 --- Thesis Organization --- p.15
Chapter 2. --- Related Work --- p.16
Chapter 2.1 --- Face Recognition for Desktop Computers --- p.16
Chapter 2.1.1 --- Global Feature Based Systems --- p.16
Chapter 2.1.2 --- Local Feature Based Systems --- p.18
Chapter 2.1.3 --- Commercial Systems --- p.20
Chapter 2.2 --- Biometrics on Mobile Devices --- p.22
Chapter 3. --- Optimization Framework --- p.24
Chapter 3.1 --- Introduction --- p.24
Chapter 3.2 --- Levels of Optimization --- p.25
Chapter 3.2.1 --- Algorithm Level --- p.25
Chapter 3.2.2 --- Code Level --- p.26
Chapter 3.2.3 --- Instruction Level --- p.27
Chapter 3.2.4 --- Architecture Level --- p.28
Chapter 3.3 --- General Optimization Workflow --- p.29
Chapter 3.4 --- Summary --- p.31
Chapter 4. --- Real Time Principal Component Analysis --- p.32
Chapter 4.1 --- Introduction --- p.32
Chapter 4.2 --- System Overview --- p.33
Chapter 4.2.1 --- Image Preprocessing --- p.33
Chapter 4.2.2 --- PCA Subspace Training --- p.34
Chapter 4.2.3 --- PCA Subspace Projection --- p.36
Chapter 4.2.4 --- Template Matching --- p.36
Chapter 4.3 --- Optimization using Fixed-point Arithmetic --- p.37
Chapter 4.3.1 --- Profiling Analysis --- p.37
Chapter 4.3.2 --- Fixed-point Representation --- p.38
Chapter 4.3.3 --- Range Estimation --- p.39
Chapter 4.3.4 --- Code Conversion --- p.42
Chapter 4.4 --- Experiments and Discussions --- p.43
Chapter 4.4.1 --- Experiment Setup --- p.43
Chapter 4.4.2 --- Execution Time --- p.44
Chapter 4.4.3 --- Space Requirement --- p.45
Chapter 4.4.4 --- Verification Accuracy --- p.45
Chapter 5. --- Real Time Elastic Bunch Graph Matching --- p.49
Chapter 5.1 --- Introduction --- p.49
Chapter 5.2 --- System Overview --- p.50
Chapter 5.2.1 --- Image Preprocessing --- p.50
Chapter 5.2.2 --- Landmark Localization --- p.51
Chapter 5.2.3 --- Feature Extraction --- p.52
Chapter 5.2.4 --- Template Matching --- p.53
Chapter 5.3 --- Optimization Overview --- p.54
Chapter 5.3.1 --- Computation Optimization --- p.55
Chapter 5.3.2 --- Memory Optimization --- p.56
Chapter 5.4 --- Optimization Strategies --- p.58
Chapter 5.4.1 --- Fixed-point Arithmetic --- p.60
Chapter 5.4.2 --- Gabor Masks and Bunch Graphs Precomputation --- p.66
Chapter 5.4.3 --- Improving Array Access Efficiency using ID array --- p.68
Chapter 5.4.4 --- Efficient Gabor Filter Selection --- p.75
Chapter 5.4.5 --- Fine Tuning System Cache Policy --- p.79
Chapter 5.4.6 --- Reducing Redundant Memory Access by Loop Merging --- p.80
Chapter 5.4.7 --- Maximizing Cache Reuse by Array Merging --- p.90
Chapter 5.4.8 --- Optimization of Trigonometric Functions using Table Lookup. --- p.97
Chapter 5.5 --- Summary --- p.99
Chapter 6. --- Conclusions --- p.103
Chapter 7. --- Bibliography --- p.106
50
"An investigation into the parameters influencing neural network based facial recognition." Thesis, 2012. http://hdl.handle.net/10210/7007.
Full textAbstract:
D.Ing.This thesis deals with an investigation into facial recognition and some variables that influence the performance of such a system. Firstly there is an investigation into the influence of image variability on the overall recognition performance of a system and secondly the performance and subsequent suitability of a neural network based system is tested. Both tests are carried out on two distinctly different databases, one more variable than the other. The results indicate that the greater the amount of variability the more negatively affected is the performance rating of a specific facial recognition system. The results further indicate the success with the implementation of a neural network system over a more conventional statistical system.