Relevant bibliographies by topics / Computer Vision Pattern Recognition / Dissertations / Theses
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Dissertations / Theses on the topic 'Computer Vision Pattern Recognition'

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Published: 4 June 2025
Last updated: 23 June 2025

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1

PAOLANTI, MARINA. "Pattern Recognition for challenging Computer Vision Applications." Doctoral thesis, Università Politecnica delle Marche, 2018. http://hdl.handle.net/11566/252904.

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La Pattern Recognition è lo studio di come le macchine osservano l'ambiente, imparano a distinguere i pattern di interesse dal loro background e prendono decisioni valide e ragionevoli sulle categorie di modelli. Oggi l'applicazione degli algoritmi e delle tecniche di Pattern Recognition è trasversale. Con i recenti progressi nella computer vision, abbiamo la capacità di estrarre dati multimediali per ottenere informazioni preziose su ciò che sta accadendo nel mondo. Partendo da questa premessa, questa tesi affronta il tema dello sviluppo di sistemi di Pattern Recognition per applicazioni reali come la biologia, il retail, la sorveglianza, social media intelligence e i beni culturali. L'obiettivo principale è sviluppare applicazioni di computer vision in cui la Pattern Recognition è il nucleo centrale della loro progettazione, a partire dai metodi generali, che possono essere sfruttati in più campi di ricerca, per poi passare a metodi e tecniche che affrontano problemi specifici. Di fronte a molti tipi di dati, come immagini, dati biologici e traiettorie, una difficoltà fondamentale è trovare rappresentazioni vettoriali rilevanti. Per la progettazione del sistema di riconoscimento dei modelli vengono eseguiti i seguenti passaggi: raccolta dati, estrazione delle caratteristiche, approccio di apprendimento personalizzato e analisi e valutazione comparativa. Per una valutazione completa delle prestazioni, è di grande importanza collezionare un dataset specifico perché i metodi di progettazione che sono adattati a un problema non funzionano correttamente su altri tipi di problemi. I metodi su misura, adottati per lo sviluppo delle applicazioni proposte, hanno dimostrato di essere in grado di estrarre caratteristiche statistiche complesse e di imparare in modo efficiente le loro rappresentazioni, permettendogli di generalizzare bene attraverso una vasta gamma di compiti di visione computerizzata.<br>Pattern Recognition is the study of how machines can observe the environment, learn to distinguish patterns of interest from their background, and make sound and reasonable decisions about the patterns categories. Nowadays, the application of Pattern Recognition algorithms and techniques is ubiquitous and transversal. With the recent advances in computer vision, we now have the ability to mine such massive visual data to obtain valuable insight about what is happening in the world. The availability of affordable and high resolution sensors (e.g., RGB-D cameras, microphones and scanners) and data sharing have resulted in huge repositories of digitized documents (text, speech, image and video). Starting from such a premise, this thesis addresses the topic of developing next generation Pattern Recognition systems for real applications such as Biology, Retail, Surveillance, Social Media Intelligence and Digital Cultural Heritage. The main goal is to develop computer vision applications in which Pattern Recognition is the key core in their design, starting from general methods, that can be exploited in more fields, and then passing to methods and techniques addressing specific problems. The privileged focus is on up-to-date applications of Pattern Recognition techniques to real-world problems, and on interdisciplinary research, experimental and/or theoretical studies yielding new insights that advance Pattern Recognition methods. The final ambition is to spur new research lines, especially within interdisciplinary research scenarios. Faced with many types of data, such as images, biological data and trajectories, a key difficulty was to nd relevant vectorial representations. While this problem had been often handled in an ad-hoc way by domain experts, it has proved useful to learn these representations directly from data, and Machine Learning algorithms, statistical methods and Deep Learning techniques have been particularly successful. The representations are then based on compositions of simple parameterized processing units, the depth coming from the large number of such compositions. It was desirable to develop new, efficient data representation or feature learning/indexing techniques, which can achieve promising performance in the related tasks. The overarching goal of this work consists of presenting a pipeline to select the model that best explains the given observations; nevertheless, it does not prioritize in memory and time complexity when matching models to observations. For the Pattern Recognition system design, the following steps are performed: data collection, features extraction, tailored learning approach and comparative analysis and assessment. The proposed applications open up a wealth of novel and important opportunities for the machine vision community. The newly dataset collected as well as the complex areas taken into exam, make the research challenging. In fact, it is crucial to evaluate the performance of state of the art methods to demonstrate their strength and weakness and help identify future research for designing more robust algorithms. For comprehensive performance evaluation, it is of great importance developing a library and benchmark to gauge the state of the art because the methods design that are tuned to a specic problem do not work properly on other problems. Furthermore, the dataset selection is needed from different application domains in order to offer the user the opportunity to prove the broad validity of methods. Intensive attention has been drawn to the exploration of tailored learning models and algorithms, and their extension to more application areas. The tailored methods, adopted for the development of the proposed applications, have shown to be capable of extracting complex statistical features and efficiently learning their representations, allowing it to generalize well across a wide variety of computer vision tasks, including image classication, text recognition and so on.
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Crossley, Simon. "Robust temporal stereo computer vision." Thesis, University of Sheffield, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.327614.

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Fletcher, Gordon James. "Geometrical problems in computer vision." Thesis, University of Liverpool, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.337166.

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Ali, Abdulamer T. "Computer vision aided road traffic analysis." Thesis, University of Bristol, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.333953.

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5

Millman, Michael Peter. "Computer vision for yarn quality inspection." Thesis, Loughborough University, 2000. https://dspace.lboro.ac.uk/2134/34196.

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Structural parameters that determine yarn quality include evenness, hairiness and twist. This thesis applies machine vision techniques to yarn inspection, to determine these parameters in a non-contact manner. Due to the increased costs of such a solution over conventional sensors, the thesis takes a wide look at, and where necessary develops, the potential uses of machine vision for several key aspects of yarn inspection at both low and high speed configurations. Initially, the optimum optical / imaging conditions for yarn imaging are determined by investigating the various factors which degrade a yarn image. The depth of field requirement for imaging yarns is analysed, and various solutions are discussed critically including apodisation, wave front encoding and mechanical guidance. A solution using glass plate guides is proposed, and tested in prototype. The plates enable the correct hair lengths to be seen in the image for long hairs, and also prevent damaging effects on the hairiness definition due to yarn vibration and yarn rotation. The optical system parameters and resolution limits of the yarn image when using guide plates are derived and optimised. The thesis then looks at methods of enhancing the yarn image, using various illumination methods, and incoherent and coherent dark-field imaging.
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Tordoff, Ben. "Active control of zoom for computer vision." Thesis, University of Oxford, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.270752.

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Hunt, Neil. "Tools for image processing and computer vision." Thesis, University of Aberdeen, 1990. http://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU025003.

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The thesis describes progress towards the construction of a seeing machine. Currently, we do not understand enough about the task to build more than the simplest computer vision systems; what is understood, however, is that tremendous processing power will surely be involved. I explore the pipelined architecture for vision computers, and I discuss how it can offer both powerful processing and flexibility. I describe a proposed family of VLSI chips based upon such an architecture, each chip performing a specific image processing task. The specialisation of each chip allows high performance to be achieved, and a common pixel interconnect interface on each chip allows them to be connected in arbitrary configurations in order to solve different kinds of computational problems. While such a family of processing components can be assembled in many different ways, a programmable computer offers certain advantages, in that it is possible to change the operation of such a machine very quickly, simply by substituting a different program. I describe a software design tool which attempts to secure the same kind of programmability advantage for exploring applications of the pipelined processors. This design tool simulates complete systems consisting of several of the proposed processing components, in a configuration described by a graphical schematic diagram. A novel time skew simulation technique developed for this application allows coarse grain simulation for efficiency, while preserving the fine grain timing details. Finally, I describe some experiments which have been performed using the tools discussed earlier, showing how the tools can be put to use to handle real problems.
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Moore, Darnell Janssen. "Vision-based recognition of actions using context." Diss., Georgia Institute of Technology, 2000. http://hdl.handle.net/1853/16346.

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Tsai, Ming-Jong. "A new technique for 3-D computer vision." Thesis, University of Liverpool, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.240784.

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Christmas, W. J. "Structural matching in computer vision using probabilistic reasoning." Thesis, University of Surrey, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.308472.

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Tu, Peter Henry. "Extracting and analysing seismic events using computer vision techniques." Thesis, University of Oxford, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.282329.

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Khendek, Hamid. "Computer optical-vision system for glass measurement and inspection." Thesis, University of Nottingham, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.283378.

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13

Griffin, A. C. "Computer vision techniques for the automatic interpretation of thermochromic paint." Thesis, University of Surrey, 2001. http://epubs.surrey.ac.uk/844526/.

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The aim of this study is to provide an automatic method for the interpretation of images of objects that are coated with thermal paint. Thermal paint changes colour permanently according to the temperature to which it is heated and can be employed as a temperature gauge where more cumbersome measurement apparatus may not be suitable. Such a gauge requires a means to convert the manifestation of the measurement to the corresponding numerical values. In our case this involves the grouping of ranges of colour together into temperature bands and the extraction of the temperature contours between these bands, a task currently performed by a human operator. This study will demonstrate some success in the automatic interpretation of thermal paints through computer vision approaches. In summary the main contributions of this work are: The demonstration that edge detection is not a useful step. Human operators tend to interpret thermochromic paint not simply by colour matching, but by locating prominent colour change points. We demonstrate why in our opinion this in not necessarily the best step through an exploration of colour edge detection. The development of a feature space model of the paint colour formation based on B-splines and the employment of this within a maximum likelihood estimation scheme [GKWG96],[CSGW97] The development of a paint interpretation method based on a Markov Random Field and Simulated Annealing [GSW+98] Our methods axe applicable to cases of ideal data. We highlight some troublesome paint artefacts that occur in real cases and that hinder interpretation. We discuss possible solutions. Finally we draw conclusions and point to directions for possible future work. Key words: thermochromic paint, maximum likelihood estimate, simulated annealing.
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Moustafa, Moustafa Abdel-Azim. "Feature recognition using a fast radon transform-based computer vision system." Thesis, Cranfield University, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.305610.

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Andrews, Michael J. "An Information Theoretic Hierarchical Classifier for Machine Vision." Digital WPI, 1999. https://digitalcommons.wpi.edu/etd-theses/807.

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A fundamental problem in machine vision is the classifcation of objects which may have unknown position, orientation, or a combination of these and other transformations. The massive amount of data required to accurately form an appearance-based model of an object under all values of shift and rotation transformations has discouraged the incorporation of the combination of both transformations into a single model representation. This Master's Thesis documents the theory and implementation of a hierarchical classifier, named the Information Theoretic Decision Tree system, which has the demonstrated ability to form appearance-based models of objects which are shift and rotation invariant which can be searched with a great reduction in evaluations over a linear sequential search. Information theory is utilized to obtain a measure of information gain in a feature space recursive segmentation algorithm which positions hyperplanes to local information gain maxima. This is accomplished dynamically through a process of local optimization based on a conjugate gradient technique enveloped by a simulated annealing optimization loop. Several target model training strategies have been developed for shift and rotation invariance, notably the method of exemplar grouping, in which any combination of rotation and translation transformations of target object views can be simulated and folded into the appearance-based model. The decision tree structure target models produced as a result of this process effciently represent the voluminous training data, according rapid test-time classification of objects.
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Hluchoweckyj, Lydia Theodosia. "Recognising road marking structures for autonomous vehicle navigation using computer vision." Thesis, University of Bristol, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.357691.

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Pan, Wendy. "A simulated shape recognition system using feature extraction /." Online version of thesis, 1989. http://hdl.handle.net/1850/10496.

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Apitz, Andreas M. "Towards a Strawberry Harvest Prediction System Using Computer Vision and Pattern Recognition." DigitalCommons@CalPoly, 2018. https://digitalcommons.calpoly.edu/theses/1858.

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Farmers require advance notice when a harvest is approaching, so they can allocate resources and hire workers as efficiently as possible. Existing methods are subjective and labor intensive, and require the expertise of a professional forecaster. Cal Poly’s EE department has been collaborating with the Cal Poly Strawberry Center to investigate the potential in using digital imaging processing to predict harvests more reliably. This paper shows the progress of that ongoing project, as well as what aspects could still be improved. Three main blocks comprise this system: data acquisition, which obtains and catalogues images of the strawberry plants; computer vision, which extracts information from the images and constructs a time-series model of the field as a whole; and prediction, which uses the field’s history to guess when the most likely harvest window will be. The best method of data acquisition is determined through a decision matrix to be a small autonomous rover. Several challenges specific to images captured via drone, such as fisheye distortion and dirt masking, are examined and mitigated. Using thresholding, the nRGB color space is shown to be the most promising for image segmentation of red strawberries. Data from field 25 at the Cal Poly Strawberry Center is tabulated, analyzed, and compared against industry trends across California. Ultimately, this work serves as a strong benchmark towards a full strawberry yield prediction system.
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黃業新 and Yip-san Wong. "A two-level model-based object recognition technique." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1995. http://hub.hku.hk/bib/B31213807.

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Wong, Yip-san. "A two-level model-based object recognition technique /." Hong Kong : University of Hong Kong, 1995. http://sunzi.lib.hku.hk/hkuto/record.jsp?B14705552.

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Pan, Xiang. "Approaches for edge detection, pose determination and object representation in computer vision." Thesis, Heriot-Watt University, 1994. http://hdl.handle.net/10399/1378.

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Lotufo, Roberto Alencar. "Computer architecture and robot vision applied to an autonomous road following vehicle." Thesis, University of Bristol, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.303749.

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Redfield, Signe Anne. "Efficient object recognition using color quantization." [Gainesville, Fla.] : University of Florida, 2001. http://purl.fcla.edu/fcla/etd/UFE0000347.

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Thesis (Ph. D.)--University of Florida, 2001.<br>Title from title page of source document. Document formatted into pages; contains xiv, 150 p.; also contains graphics. Includes vita. Includes bibliographical references.
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Zheng, Yue Chu. "Feature extraction for chart pattern classification in financial time series." Thesis, University of Macau, 2018. http://umaclib3.umac.mo/record=b3950623.

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Woo, Myung Chul. "Biologically-inspired translation, scale, and rotation invariant object recognition models /." Online version of thesis, 2007. http://hdl.handle.net/1850/3933.

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Costa, Mauro Sergio Figueiredo. "Object recognition and pose estimation using appearance-based features and relational indexing /." Thesis, Connect to this title online; UW restricted, 1997. http://hdl.handle.net/1773/6055.

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Johnson, Abioseh Saeley. "Automatic number-plate recognition : an application of computer vision technology to automatic vehicle identification." Thesis, University of Bristol, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.300053.

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Koubaroulis, D. A. "The multimodal neighbourhood signature for modelling object colour appearance and applications in computer vision." Thesis, University of Surrey, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.365142.

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Sun, Shijun. "Video object segmentation and tracking using VSnakes /." Thesis, Connect to this title online; UW restricted, 2000. http://hdl.handle.net/1773/6038.

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Ekinci, Murat. "Computer vision applied to the navigation of an autonomous road vehicle in complex road networks." Thesis, University of Bristol, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.361132.

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Liu, Chang. "Human motion detection and action recognition." HKBU Institutional Repository, 2010. http://repository.hkbu.edu.hk/etd_ra/1108.

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Giordano, Anthony J. "What can your computer recognize chemical and facial pattern recognition through the use of Eigen Analysis Method /." [Denver, Colo.] : Regis University, 2007. http://165.236.235.140/lib/AGiordanoPartI2007.pdf.

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Henderson, Drake Hall. "Accelerated partial window imaging in an integrated vision unit." Thesis, Georgia Institute of Technology, 1995. http://hdl.handle.net/1853/16630.

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TESFAYE, YONATAN TARIKU. "Applications of a graph theoretic based clustering framework in computer vision and pattern recognition." Doctoral thesis, Università IUAV di Venezia, 2018. http://hdl.handle.net/11578/282321.

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Kolesnik, Paul. "Conducting gesture recognition, analysis and performance system." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=81499.

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A number of conducting gesture analysis and performance systems have been developed over the years. However, most of the previous projects either primarily concentrated on tracking tempo and amplitude indicating gestures, or implemented individual mapping techniques for expressive gestures that varied from research to research. There is a clear need for a uniform process that could be applied toward analysis of both indicative and expressive gestures. The proposed system provides a set of tools that contain extensive functionality for identification, classification and performance with conducting gestures. Gesture recognition procedure is designed on the basis of Hidden Markov Model (HMM) process. A set of HMM tools are developed for Max/MSP software. Training and recognition procedures are applied toward both right-hand beat- and amplitude-indicative gestures, and left-hand expressive gestures. Continuous recognition of right-hand gestures is incorporated into a real-time gesture analysis and performance system in Eyesweb and Max/MSP/Jitter environments.
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Chen, Quanxin. "Camera calibration and shape recovery from videos of two mirrors." HKBU Institutional Repository, 2015. https://repository.hkbu.edu.hk/etd_oa/168.

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Mirrors are often studied for camera calibration since they provide symmetric relationship for object which can guarantee synchronization in multiple views. However, it is sometimes difficult to compute the reflection matrices of mirrors. This thesis aims to solve the problem of camera calibration and shape recovery from a two-mirror system which is able to generate five views of an object. It firstly studies the similarity relationship of the motion formed by the five views in two-mirror system with the circular motion. It is shown that the motion formed by the five views can be regarded as two circular motions so that we can avoid computing the reflection matrices of mirrors. This thesis then shows the most important problem which is to recover the vanishing line of rotation plane and the imaged circular points by two unknown equal angles via metric rectification. After that, it is easy to recover the imaged rotation axis and the vanishing points X-axis via imaged circular points. Different from the state-of-the-art algorithm, this thesis avoid computing vanishing points X-axis at first because it will cause accumulative error when recovering the imaged rotation axis. By now it is enough to compute the camera intrinsics which is the main objective of this thesis. At last, a 3D visual hull model of object could be reconstructed once all the projective matrices of views were computed. This thesis uses a short video instead of static snapshots so that the reconstructed 3D visual hull model of each frame can be put together based on the motion sequence of object to make a 3D animation. This animation can help to boost the accuracy of action recognition in contrast to 2D video. In general, the action recognition by 2D videos always distinguishes action according to the side of human taken by videos but cannot do for the side does not appear in videos. It then requires to store every direction for human actions of video into database which causes redundancy. The 3D animation can deal with this problem since the reconstructed model can be seen in every direction so that only one 3D animation of human action is needed to store in database. The experimental results show that the more frames are used, the less error of camera intrinsics will occur and the reconstructed 3D model shows the feasibility of the approach.
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Johnson, Andrew. "Fragment Association Matching Enhancement (FAME) on a Video Tracker." Wright State University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=wright1399465180.

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Jacobs, Emmerentia. "Deterministic tracking using active contours." Thesis, Link to the online version, 2005. http://hdl.handle.net/10019/1055.

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Vincent-Humphreys, Diane Lesley de. "A gestural recognition interface using machine vision : towards improving computer interaction for people with severe motor disabilities." Thesis, Coventry University, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.362648.

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Prokaj, Jan. "DETECTING CURVED OBJECTS AGAINST CLUTTERED BACKGROUNDS." Master's thesis, University of Central Florida, 2008. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2847.

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Detecting curved objects against cluttered backgrounds is a hard problem in computer vision. We present new low-level and mid-level features to function in these environments. The low-level features are fast to compute, because they employ an integral image approach, which makes them especially useful in real-time applications. The mid-level features are built from low-level features, and are optimized for curved object detection. The usefulness of these features is tested by designing an object detection algorithm using these features. Object detection is accomplished by transforming the mid-level features into weak classifiers, which then produce a strong classifier using AdaBoost. The resulting strong classifier is then tested on the problem of detecting heads with shoulders. On a database of over 500 images of people, cropped to contain head and shoulders, and with a diverse set of backgrounds, the detection rate is 90% while the false positive rate on a database of 500 negative images is less than 2%.<br>M.S.<br>School of Electrical Engineering and Computer Science<br>Engineering and Computer Science<br>Computer Science MS
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Van, der Elst Herman. "Coding of virtual human motion." Thesis, University of Pretoria, 1999. http://hdl.handle.net/2263/27728.

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Please read the abstract in the section 00front of this document<br>Thesis (PhD (Electronic Engineering))--University of Pretoria, 2007.<br>Electrical, Electronic and Computer Engineering<br>unrestricted
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Hoang, Thai V. "Image Representations for Pattern Recognition." Phd thesis, Université Nancy II, 2011. http://tel.archives-ouvertes.fr/tel-00714651.

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La pertinence d'une application de traitement de signal relève notamment du choix d'une "représentation adéquate''. Par exemple, pour la reconnaissance de formes, la représentation doit mettre en évidence les propriétés salientes d'un signal; en débruitage, permettre de séparer le signal du bruit; ou encore en compression, de synthétiser fidèlement le signal d'entrée à l'aide d'un nombre réduit de coefficients. Bien que les finalités de ces quelques traitements soient distinctes, il apparait clairement que le choix de la représentation impacte sur les performances obtenues. La représentation d'un signal implique la conception d'un ensemble génératif de signaux élémentaires, aussi appelé dictionnaire ou atomes, utilisé pour décomposer ce signal. Pendant de nombreuses années, la conception de dictionnaire a suscité un vif intérêt des chercheurs dans des domaines applicatifs variés: la transformée de Fourier a été employée pour résoudre l'équation de la chaleur; celle de Radon pour les problèmes de reconstruction; la transformée en ondelette a été introduite pour des signaux monodimensionnels présentant un nombre fini de discontinuités; la transformée en contourlet a été conçue pour représenter efficacement les signaux bidimensionnels composées de régions d'intensité homogène, à frontières lisses, etc. Jusqu'à présent, les dictionnaires existants peuvent être regroupés en deux familles d'approches: celles s'appuyant sur des modèles mathématiques de données et celles concernant l'ensemble de réalisations des données. Les dictionnaires de la première famille sont caractérisés par une formulation analytique. Les coefficients obtenus dans de telles représentations d'un signal correspondent à une transformée du signal, qui peuvent parfois être implémentée rapidement. Les dictionnaires de la seconde famille, qui sont fréquemment des dictionnaires surcomplets, offrent une grande flexibilité et permettent d'être adaptés aux traitements de données spécifiques. Ils sont le fruit de travaux plus récents pour lesquels les dictionnaires sont générés à partir des données en vue de la représentation de ces dernières. L'existence d'une multitude de dictionnaires conduit naturellement au problème de la sélection du meilleur d'entre eux pour la représentation de signaux dans un cadre applicatif donné. Ce choix doit être effectué en vertu des spécificités bénéfiques validées par les applications envisagées. En d'autres termes, c'est l'usage qui conduit à privilégier un dictionnaire. Dans ce manuscrit, trois types de dictionnaire, correspondant à autant de types de transformées/représentations, sont étudiés en vue de leur utilisation en analyse d'images et en reconnaissance de formes. Ces dictionnaires sont la transformée de Radon, les moments basés sur le disque unitaire et les représentations parcimonieuses. Les deux premiers dictionnaires sont employés pour la reconnaissance de formes invariantes tandis que la représentation parcimonieuse l'est pour des problèmes de débruitage, de séparation des sources d'information et de classification. Cette thèse présentent des contributions théoriques validées par de nombreux résultats expérimentaux. Concernant la transformée de Radon, des pistes sont proposées afin d'obtenir des descripteurs de formes invariants, et conduisent à définir deux descripteurs invariants aux rotations, l'échelle et la translation. Concernant les moments basés sur le disque unitaire, nous formalisons les stratégies conduisant à l'obtention de moments orthogonaux. C'est ainsi que quatre moments harmoniques polaires génériques et des stratégies pour leurs calculs rapides sont introduits. Enfin, concernant les représentations parcimonieuses, nous proposons et validons un formalisme de représentation permettant de combiner les trois critères suivant : la parcimonie, l'erreur de reconstruction ainsi que le pouvoir discriminant en classification.
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Lebo, Timothy M. "Guiding object recognition : a shape model with co-activation networks /." Link to online version, 2005. http://hdl.handle.net/1850/993.

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Rao, Zusheng. "Optimal algorithms for object recognition with occlusion in scale space." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ39223.pdf.

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Ma, Jinhua. "Dependency modeling for information fusion with applications in visual recognition." HKBU Institutional Repository, 2013. https://repository.hkbu.edu.hk/etd_ra/1522.

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Chen, Jingni. "Correlated topic random field for simultaneous object recognition and segmentation /." View abstract or full-text, 2009. http://library.ust.hk/cgi/db/thesis.pl?CSED%202009%20CHENJN.

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Jackway, Paul Thomas. "Morphological scale-space with application to three-dimensional object recognition." Thesis, Queensland University of Technology, 1994.

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48

Page, Gavin S. "An investigation of techniques in deformable object recognition /." Link to online version, 2005. https://ritdml.rit.edu/dspace/handle/1850/1184.

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Higgs, David Robert. "Parts-based object detection using multiple views /." Link to online version, 2005. https://ritdml.rit.edu/dspace/handle/1850/1000.

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Bressan, Marco José Miguel. "Statistical Independence for classification for High Dimensional Data." Doctoral thesis, Universitat Autònoma de Barcelona, 2003. http://hdl.handle.net/10803/3034.

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