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Amaral, Wagner Machado do 1986. "Rastreamento de pessoas em vídeo." [s.n.], 2013. http://repositorio.unicamp.br/jspui/handle/REPOSIP/258880.
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Orientador: Clésio Luis TozziDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação
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Resumo: O barateamento das câmeras de vídeo e o crescente poder de processamento dos computadores tem tornado a vigilância por vídeo um meio acessível e eficaz para monitorar espaços públicos e privados. Nesse contexto, o rastreamento de pessoas por vídeo tem motivado inúmeros trabalhos. O objetivo de um sistema de rastreamento de pessoas e determinar a trajetória das pessoas presentes no vídeo com base na variação de suas posições em cada quadro. Embora as soluções proposta na literatura para resolver o problema do rastreamento apresentem constante evolução, obter as trajetórias das pessoas ainda e um desafio no campo da visão computacional. O presente trabalho aborda aspectos do rastreamento de pessoas em vídeos e propõe um sistema de rastreamento baseado em abordagens descritas na literatura. O sistema proposto nesse trabalho e dividido em duas etapas principais: Detecção do foreground e Calculo das Trajetórias. A etapa de detecção do foreground consiste na detecção das regiões na imagem correspondentes aos alvos a serem seguidos e divididos em três partes: subtração de fundo, remoção de sombras e remoção de ruídos por morfologia matemática. A etapa do calculo das trajetórias e dividida em duas partes: Associação e Gerenciamento das Pessoas Seguidas. A associação corresponde ao processamento realizado em cada quadro, onde as regiões do foreground são associadas às pessoas seguidas com base em métricas relacionadas ao centróide, bounding box e histograma de cor. Durante oclusões um método de detecção de cabeças e utilizado. O gerenciamento das pessoas seguidas corresponde a um procedimento mais amplo, no qual se analisa o deslocamento de todas as pessoas presentes na cena. O sistema proposto no presente trabalho e aplicado a vídeos de bases publicas. Para cada vídeo testado, informações relacionadas ao numero de pessoas no vídeo e suas posições são obtidas manualmente e comparadas aos resultados obtidos através do sistema proposto
Abstract: The increasing of computer power has turned video surveillance into an effective and affordable means to monitor public and private areas. In this context, tracking systems is motivating researchers around the world. The main goal of a tracking system is to determine the location or direction of a target in each video frame. Although the proposed solutions for tracking problems have been improved continuously, people path detection is still a challenge in computer vision field. This work discusses the main aspects of people tracking in video and proposes an implementation based on approaches described in the literature. The system is divided into two main steps: foreground detection and trajectory calculation. The foreground detection step consists of three parts: background subtraction, shadow suppression and noise removal by morphological image processing. The trajectory calculation step is divided into two parts: matching and trajectory management. The matching is performed in each video frame to associate the foreground image regions and the tracked elements. In the implemented system matching metrics related to the centroid position, bounding box and color histogram are used. In case of occlusion a head detection method is employed. In the trajectory management procedure the foreground objects are analyzed and recorded. Public datasets were used to evaluate the system efficiency
Mestrado
Engenharia de Computação
Mestre em Engenharia Elétrica
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Edman, Viktor. "Tracking Groups of People in Video Surveillance." Thesis, Linköpings universitet, Reglerteknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-93996.
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In this master thesis, the problem of tracking groups using an image sequence dataset is examined. Target tracking can be defined as the problem of estimating a target's state given prior knowledge about its motion and some sensor measurements related to the target's state. A popular method for target tracking is e.g. the Kalman filter. However, the Kalman filter is insufficient when there are multiple targets in the scene. Consequently, alternative multitarget tracking methods must be applied along with methods for estimating the number of targets in the scene. Multitarget tracking can however be difficult when there are many unresolved targets, e.g. associating observations with targets in dense crowds. A viable simplification is group target tracking, keeping track of groups rather than individual targets. Furthermore, group target tracking is preferred when the user wants to know the motion and extension of a group in e.g. evacuation scenarios. To solve the problem of group target tracking in video surveillance, a combination of GM-PHD filtering and mean shift clustering is proposed. The GM-PHD filter is an approximation of Bayes multitarget filter. Pedestrian detections converted into flat world coordinates from the image dataset are used as input to the filter. The output of the GM-PHD filter consists of Gaussian mixture components with corresponding mean state vectors. The components are divided into groups by using mean shift clustering. An estimate of the number of members and group shape is presented for each group. The method is evaluated using both single camera measurements and two cameras partly surveilling the same area. The results are promising and present a nice visual representation of the groups' characteristics. However, using two cameras gives no improvement in performance, probably due to differences in detections between the two cameras, e.g. a single pedestrian can be observed being at two positions several meters apart making it difficult to determine if it is a single pedestrian or multiple pedestrians.
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Dulai, Amanjit. "Detecting and tracking people in real-time." Thesis, Imperial College London, 2013. http://hdl.handle.net/10044/1/25096.
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The problem of detecting and tracking people in images and video has been the subject of a great deal of research, but remains a challenging task. Being able to detect and track people would have an impact in a number of fields, such as driverless vehicles, automated surveillance, and human-computer interaction. The difficulties that must be overcome include coping with variations in appearance between different people, changes in lighting, and the ability to detect people across multiple scales. As well as having high accuracy, it is desirable for a technique to evaluate an image with low latency between receiving the image and producing a result. This thesis explores methods for detecting and tracking people in images and video. Techniques are implemented on a desktop computer, with an emphasis on low latency. The problem of detection is examined first. The well established integral channel features detector is introduced and reimplemented, and various novelties are implemented in regards to the features used by the detector. Results are given to quantify the accuracy and the speed of the developed detectors on the INRIA person dataset. The method is further extended by examining the prospect of using multiple classifiers in conjunction. It is shown that using a classifier with a version of the same classifier reflected in the vertical axis can improve performance. A novel method for clustering images of people to find modes of appearance is also presented. This involves using boosting classifiers to map a set of images to vectors, to which K-means clustering is applied. Boosting classifiers are then trained on these clustered datasets to create sets of multiple classifiers, and it is demonstrated that these sets of classifiers can be evaluated on images with only a small increase in the running time over single classifiers. The problem of single target tracking is addressed using the mean shift algorithm. Mean shift tracking works by finding the best colour match for a target from frame to frame. A novel form of mean shift tracking through scale is developed, and the problem of multiple target tracking is addressed by using boosting classifiers in conjunction with Kalman filters. Tests are carried out on the CAVIAR dataset, which gives representative examples of surveillance scenarios, to show the performance of the proposed approaches.
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Silva, João Miguel Ferreira da. "People and object tracking for video annotation." Master's thesis, Faculdade de Ciências e Tecnologia, 2012. http://hdl.handle.net/10362/8953.
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Dissertação para obtenção do Grau de Mestre em
Engenharia InformáticaObject tracking is a thoroughly researched problem, with a body of associated literature dating at least as far back as the late 1970s. However, and despite the development of some satisfactory real-time trackers, it has not yet seen widespread use. This is not due to a lack of applications for the technology, since several interesting ones exist. In this document, it is postulated that this status quo is due, at least in part, to a lack of easy to use software libraries supporting object tracking. An overview of the problems associated with object tracking is presented and the process of developing one such library is documented. This discussion includes how to overcome problems like heterogeneities in object representations and requirements for training or initial object position hints. Video annotation is the process of associating data with a video’s content. Associating data with a video has numerous applications, ranging from making large video archives or long videos searchable, to enabling discussion about and augmentation of the video’s content. Object tracking is presented as a valid approach to both automatic and manual video annotation, and the integration of the developed object tracking library into an existing video annotator, running on a tablet computer, is described. The challenges involved in designing an interface to support the association of video annotations with tracked objects in real-time are also discussed. In particular, we discuss our interaction approaches to handle moving object selection on live video, which we have called “Hold and Overlay” and “Hold and Speed Up”. In addition, the results of a set of preliminary tests are reported.
project “TKB – A Transmedia Knowledge Base for contemporary dance” (PTDC/EA /AVP/098220/2008 funded by FCT/MCTES), the UTAustin – Portugal, Digital Media Program (SFRH/BD/42662/2007 FCT/MCTES) and by CITI/DI/FCT/UNL (Pest-OE/EEI/UI0527/2011)
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Morate, Villagrasa Alejandro. "People detecting and tracking using laser and vision." Thesis, KTH, Reglerteknik, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-107536.
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As part of design of a personal robot for operation in an everyday environment thereis need to endow the system with facilities to track a person as it is taken on a tour of theenvironment. In the literature a number of different methods based on laser tracking and computer vision have been presented. However, most of these methods are not particularly robust and in many cases the methods do not operate in realtime. In this master thesis a system for people detecting and tracking has been implemented using laser and vision. The information given by both scanners are used for two different purposes, laser range data are used to detect persons and the images grabbed by the camera are used to confirm the hypotheses made by the laser. Methods for people tracking based on laser and vision have two main problems. The ones based on laser are not very robust and the ones based on vision hardly ever operate in real time. This project is aimed at taking the main advantages of both methods: Laser Advantage: High Speed => Works in real time Disadvantage: Not robust => Not reliable 100% Vision: Advantage: Robust => More reliable Disadvantage: Low speed => Does not work in real time
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Limprasert, Wasit. "Real-time people tracking in a camera network." Thesis, Heriot-Watt University, 2012. http://hdl.handle.net/10399/2714.
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Visual tracking is a fundamental key to the recognition and analysis of human behaviour. In this thesis we present an approach to track several subjects using multiple cameras in real time. The tracking framework employs a numerical Bayesian estimator, also known as a particle lter, which has been developed for parallel implementation on a Graphics Processing Unit (GPU). In order to integrate multiple cameras into a single tracking unit we represent the human body by a parametric ellipsoid in a 3D world. The elliptical boundary can be projected rapidly, several hundred times per subject per frame, onto any image for comparison with the image data within a likelihood model. Adding variables to encode visibility and persistence into the state vector, we tackle the problems of distraction and short-period occlusion. However, subjects may also disappear for longer periods due to blind spots between cameras elds of view. To recognise a desired subject after such a long-period, we add coloured texture to the ellipsoid surface, which is learnt and retained during the tracking process. This texture signature improves the recall rate from 60% to 70-80% when compared to state only data association. Compared to a standard Central Processing Unit (CPU) implementation, there is a signi cant speed-up ratio.
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Moradiannejad, Ghazaleh. "People Tracking Under Occlusion Using Gaussian Mixture Model and Fast Level Set Energy Minimization." Thèse, Université d'Ottawa / University of Ottawa, 2013. http://hdl.handle.net/10393/24304.
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Tracking multiple articulated objects (such as a human body) and handling occlusion between them is a challenging problem in automated video analysis. This work proposes a new approach for accurately and steadily visual tracking people, which should function even if the system encounters occlusion in video sequences. In this approach, targets are represented with a Gaussian mixture, which are adapted to regions of the target automatically using an EM-model algorithm. Field speeds are defined for changed pixels in each frame based on the probability of their belonging to a particular person's blobs. Pixels are matched to the models using a fast numerical level set method. Since each target is tracked with its blob's information, the system is capable of handling partial or full occlusion during tracking. Experimental results on a number of challenging sequences that were collected in non-experimental environments demonstrate the effectiveness of the approach.
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Mashad, Nemati Hassan. "Detection and Tracking of People from Laser Range Data." Thesis, Högskolan i Halmstad, Halmstad Embedded and Intelligent Systems Research (EIS), 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-6102.
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In this thesis report, some of the most promising techniques, in the field of intelligent vehicles and mobile robotics, for detection and tracking of moving objects in an indoor environment are investigated. Kalman filter (KF), extended Kalman filter (EKF), and particle filters (PF) based techniques for the tracking of people are implemented and evaluated. A heuristic method is then proposed to improve the performance of the EKF based tracking in situations where moving objects are hidden by obstacles. The proposed method is based on points of maximum uncertainty (PMU) in occlusion situations and its complexity and accuracy is compared with PF method. The EKF, PF and PMU based methods are examined and compared using experimental data which are extracted by a laser range finder in an indoor environment with predefined hinders and people as the moving objects.
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Boschini, Matteo. "A deep learning-based approach for 3D people tracking." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/11321/.
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Questa tesi si occupa dell’estensione di un framework software finalizzato all'individuazione e al tracciamento di persone in una scena ripresa da telecamera stereoscopica.
In primo luogo è rimossa la necessità di una calibrazione manuale offline del sistema sfruttando algoritmi che consentono di individuare, a partire da un fotogramma acquisito dalla camera, il piano su cui i soggetti tracciati si muovono.
Inoltre, è introdotto un modulo software basato su deep learning con lo scopo di migliorare la precisione del tracciamento. Questo componente, che è in grado di individuare le teste presenti in un fotogramma, consente ridurre i dati analizzati al solo intorno della posizione effettiva di una persona, escludendo oggetti che l’algoritmo di tracciamento sarebbe portato a individuare come persone.
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Hou, Yali, and 侯亚丽. "Video-based people counting and crowd segmentation." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B47032339.
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Cielniak, Grzegorz. "People Tracking by Mobile Robots using Thermal and Colour Vision." Doctoral thesis, Örebro : Örebro universitetsbibliotek, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-1111.
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Chang, Ting-Hsun. "Robust tracking of multiple people using two widely separated cameras." Thesis, Queen Mary, University of London, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.249644.
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Joubert, Pierre. "Thermal and colour data fusion for people detection and tracking." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/86453.
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Thesis (MSc)--Stellenbosch University, 2014.ENGLISH ABSTRACT: In this thesiswe approach the problem of tracking multiple people individually in a video sequence. Automatic object detection and tracking is non-trivial as humans have complex and mostly unpredictable movements, and there are sensor noise and measurement uncertainties present. We consider traditional object detection methods and decide to use thermal data for the detection step. This choice is supported by the robustness of thermal data compared to colour data in unfavourable lighting conditions and in surveillance applications. A drawback of using thermal data is that we lose colour information, since the sensor interprets the heat emission of the body rather than visible light. We incorporate a colour sensor which is used to build features for each detected object. These features are used to help determine correspondences in detected objects over time. A problem with traditional blob detection algorithms, which typically consist of background subtraction followed by connected-component labelling, is that objects can appear to split or merge, or disappear in a few frames. We decide to add ‘dummy’ blobs in an effort to counteract these problems. We refrain from making any hard decisions with respect to the blob correspondences over time, and rather let the system decide which correspondences are more probable. Furthermore, we find that the traditional Markovian approach of determining correspondences between detected blobs in the current time step and only the previous time step can lead to unwanted behaviour. We rather consider a sequence of time steps and optimize the tracking across them. We build a composite correspondence model and weigh each correspondence according to similarity (correlation) in object features. All possible tracks are determined through this model and a likelihood is calculated for each. Using the best scoring tracks we then label all the detections and use this labelling as measurement input for a tracking filter. We find that the window tracking approach shows promise even though the data we us for testing is of poor quality and noisy. The system struggles with cluttered scenes and when a lot of dummy nodes are present. Nonetheless our findings act as a proof of concept and we discuss a few future improvements that can be considered.
AFRIKAANSE OPSOMMING: In hierdie tesis benader ons die probleemomverskeiemense individueel in ’n video-opname op te spoor en te volg. Outomatiese voorwerp-opsporing en -volging is nie-triviaal, want mense het komplekse en meestal onvoorspelbare bewegings, en daar is sensor-ruis en metingonsekerhede teenwoordig. Ons neem tradisionele voorwerp-opsporing metodes in ag en besluit om termiese data te gebruik vir die opsporingstap. Hierdie keuse word ondersteun deur die robuustheid van termiese data in vergelyking met kleur data in ongunstige lig-kondisies en in sekuriteitstoepassings. Die nadeel van die gebruik van termiese data is dat ons kleur inligting verloor, aangesien die sensor die hitte vrystelling van die liggaam interpreteer, eerder as sigbare lig. Ons inkorporeer ’n kleur-sensor wat gebruik word om die kenmerke van elke gevolgde voorwerp te bou. Hierdie kenmerke word gebruik om te help om ooreenkomste tussen opgespoorde voorwerpe te bepaal met die verloop van tyd. ’n Probleem met die tradisionele voorwerp-opsporing algoritmes, wat tipies bestaan uit agtergrond- aftrekking gevolg deur komponent-etikettering, is dat dit kan voorkom asof voorwerpe verdeel of saamsmelt, of verdwyn in ’n paar rame. Ons besluit om ‘flous’-voorwerpe by te voeg in ’n poging om hierdie probleme teen te werk. Ons weerhou om enige konkrete besluite oor opgespoorde voorwerpe se ooreenkomste met die verloop van tyd te maak, en laat die stelsel eerder toe om te besluit watter ooreenkomste meer waarskynlik is. Verder vind ons dat die tradisionele Markoviaanse benadering vir die bepaling van ooreenkomste tussen opgespoorde voorwerpe in die huidige tydstap en die vorige een kan lei tot ongewenste gedrag. Ons oorweeg eerder ’n reeks van tydstappe, of ’n venster, en optimeer die volg van voorwerpe oor hulle. Ons bou ’n saamgestelde ooreenstemmingsmodel en weeg elke ooreenstemming volgens die ooreenkoms (korrelasie) tussen voorwerpe se kenmerke. Alle moontlike spore word deur hierdie model bepaal en ’n waarskynlikheid word bereken vir elkeen. Die spore met die beste tellings word gebruik om al die opsporings te nommeer, en hierdie etikettering word gebruik as meting-inset vir ’n volgingsfilter. Ons vind dat die venster-volg benadering belowend vaar selfs al is die invoerdata in ons toetse van swak gehalte en ruiserig. Die stelsel sukkel met besige tonele en wanneer baie flous-voorwerpe teenwoordig is. Tog dien ons bevindinge as ’n bewys van konsep en ons bespreek ’n paar verbeterings wat in die toekoms oorweeg kan word.
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Lee, Yeongseon. "Bayesian 3D multiple people tracking using multiple indoor cameras and microphones." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/29668.
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Thesis (Ph.D)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009.Committee Chair: Rusell M. Mersereau; Committee Member: Biing Hwang (Fred) Juang; Committee Member: Christopher E. Heil; Committee Member: Georgia Vachtsevanos; Committee Member: James H. McClellan. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Hyman, Jacob A. (Jacob Andrew) 1980. "Computer vision based people tracking for motivating behavior in public spaces." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/28465.
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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.Includes bibliographical references (p. 121-125).
In this work a system that automates the process of people counting to determine what effects "just-in-time" messages have on motivating behavior is described. The system is designed to permit automatic study of the impact of motivational messages on people's stair use. A projector presents a point-of-decision message to passers-by choosing between a set of stairs and an escalator while a computer vision algorithm counts each type of traffic. Preliminary results of the effects of messages displayed in a Boston area subway station are discussed. The system is designed to be easily moved to different locations with minimal change to the setup and algorithm. Results from an initial trail showed a 4.3% increase in stair usage (p < .001), demonstrating both the viability of the measurement technology and the potential of point-of-decision messaging to change behavior.
by Jacob A. Hyman.
M.Eng.
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Führ, Gustavo. "Pedestrian tracking and collective behavior recognition." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2017. http://hdl.handle.net/10183/157971.
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A análise de comportamento coletivo e rastreamento de pedestres apresentam diversas aplicações, especialmente em sistemas de vigilância inteligente. Neste trabalho é proposta uma solução compreensiva com objetivo de atingir rastreamento de pedestre e reconhecimento de atividade coletiva de maneira robusta baseada na utilização de câmeras calibradas. Primeiramente, com o objetivo de remover a necessidade de calibração manual, nós apresentamos um método de calibração automática que explora detectores de pedestres e remoção de fundo para calibragem baseada em otimização não-linear. Adicionalmente, nós propomos a utilização da matriz de calibração para gerar candidatos coerentes com a geometria de cena em detectores de pedestres. Nossa abordagem tem como objetivo diminuir o intervalo de escalas comumente utilizado em detectores baseados em janelas deslizantes, gerando um número menor de extrações de atributos e reduzindo o número de falsos positivos na detecção. Em seguida, nós propomos um método de rastreamento de múltiplos pedestres utilizando câmeras calibradas. Nossa abordagem explora histogramas de cor para rastrear os pequenas regiões (patches) de cada alvo. Os vetores de deslocamento obtidos através do pareamento de atributos de aparência são combinados com um vetor obtido através de um preditor de movimento em coordenadas de mundo. Adicionalmente, nós incluímos informações originárias de detectores de pedestres para aumentar a acurácia do sistema e sua habilidade de recuperação a falhas. Por fim, nós propomos uma abordagem hierárquica de duas camadas para o problema de reconhecimento de atividade coletiva baseada no uso de classificadores Random Forests. No primeiro nível da técnica proposta, nós utilizamos distâncias entre pares de pessoas e suas respectivas velocidades relativas para classificar interações de pares. Estas interações são combinadas com a dinâmica do formato do grupo observado (e sua respectiva velocidade) para o reconhecimento de atividades coletivas. Os experimentos realizados neste trabalho demonstram a qualidade de nossas abordagens em sequências de vídeos disponíveis publicamente. Nossos resultados mostram serem competitivos quando comparados com técnicas do estado da arte e, particularmente, apresentam uma boa generalização entre diferentes cenários de captura de vídeo.Collective behavior detection and pedestrian tracking present many applications, specially in surveillance systems. In this dissertation, we proposed a complete pipeline for achieving robust tracking and collective behavior recognition based on calibrated static cameras. To remove the necessity of manual calibration, we first present a fully automatic self-calibration system that explores pedestrian detection results and background removal at non-consecutive frames in order to calibrate a static camera using a non-linear cost function. We also propose the use of camera calibration to generate geometrically coherent candidates for pedestrian detection. Our approach aims to reduce the scale range typically used in sliding-window techniques, which leads to less feature extractions and decreased number of false positives. Then, we propose a multi-target pedestrian tracking algorithm using a calibrated static camera. The tracking approach explores color histograms to track patches of each target. Obtained displacement vectors are combined with the expected motion of pedestrians in the world coordinate system. The proposed tracker also incorporates pedestrian detector results to improve the system’s accuracy and its ability to recover from failure. Finally, we propose a two-layered approach for collective behavior recognition based on Random Forests classifiers. In the first level, we use inter-personal distances and relative speeds computed in the world coordinate system to classify asymmetrical pair interactions. Those interactions are combined with group shape dynamics and mean velocity to recognize the collective behavior. We devise a set of experiments to attest the quality of our approaches using publicly available datasets. Results have shown to be competitive against state-of-the-art techniques, and particularly of good generalization across different databases.
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Luber, Matthias [Verfasser], and Kai O. [Akademischer Betreuer] Arras. "People tracking under social constraints = Bewegungsnachführung von Fußgängern unter Berücksichtung sozialer Randbedingungen." Freiburg : Universität, 2014. http://d-nb.info/1114829358/34.
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Cheung, Owen Ou Loung. "A biologically motivated system for tracking moving people using a stationary camera." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ29583.pdf.
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Tang, Siyu [Verfasser], and Bernt [Akademischer Betreuer] Schiele. "People detection and tracking in crowded scenes / Siyu Tang ; Betreuer: Bernt Schiele." Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2017. http://d-nb.info/1142919722/34.
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Colombo, Alberto. "Tracking people across multiple cameras in the presence of clutter and noise." Thesis, Kingston University, 2011. http://eprints.kingston.ac.uk/21805/.
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As video surveillance systems become more and more pervasive in our society, it is evident that simply increasing the number of cameras does not guarantee increased security, since each operator can only attend to a limited number of monitors. To overcome this limit, automatic video surveillance systems (AVSS, computer-based surveillance systems that automate some of the most tedious work of security operators) are being deployed. One such task is tracking, defined by the end users in this project as "keeping a selected passenger always visible on a surveillance monitor". The purpose of this work was to develop a single-person, multi-camera tracker that can be used in real time to follow a manually-selected individual. The operation of selecting an individual for tracking is called tagging, and therefore this type of tracker is known as a tag and track system. The developed system is conceived to be deployed as part of a large surveillance network, consisting of possibly hundreds of cameras, with possibly large blind regions between cameras. The main contribution of this thesis is a probabilistic framework that can be used to develop a multi-camera tracker by fusing heterogeneous information coming from visual sensors and from prior knowledge about the relative poisitioning of cameras in the surveillance network. The developed tracker has been demonstrated to work in real time on a standard PC independently of the number of cameras in the network. The developed tracker has been demonstrated to work in real time on a standard PC independently of the number of cameras in the network. Quantitative performance evaluation is carried out using realistic tracking scenarios.
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Harvey, Nicholas Keller James M. "Estimation and tracking of elder activity levels for health event prediction." Diss., Columbia, Mo. : University of Missouri--Columbia, 2009. http://hdl.handle.net/10355/6657.
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Title from PDF of title page (University of Missouri--Columbia, viewed on March 10, 2010). The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file. Thesis advisor: Dr. James Keller. Includes bibliographical references.
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Rytwinski, Nina Katherine. "Do people with symptoms of depression exhibit a negative attentional bias or depressive evenhandedness?" Kent State University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=kent1276562437.
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Bellotto, Nicola. "Multisensor data fusion for simultaneous people tracking and recognition with a service robot." Thesis, University of Essex, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.495813.
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Modern service robots are designed to operate in private and public areas characterized by the presence of people. In order to move safely in the environment and provide useroriented services, these robots need to estimate the position and the identity of humans. Such a task, however, is made particularly difficult by the uncertainty of robot's observations and by the dynamic nature of human environments. The methods and the algorithms implemented have been extensively tested with mobile robots in dynamic human envhonments, evaluating the performance of the people tracking and recognition in many challenging situations. The solutions adopted include a number of contributions in the challenging areas of human-centred robotics and multisensor perception.
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Hofmann, Martin [Verfasser]. "Detection, Tracking and Gait-Based Identification of Multiple People in Videos / Martin Hofmann." München : Verlag Dr. Hut, 2013. http://d-nb.info/1045989258/34.
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Hughes, T. L. "A technique to enable the tracking of people for domestic energy monitoring applications." Thesis, University of Salford, 2015. http://usir.salford.ac.uk/36159/.
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Domestic energy consumption has increasingly become a cause for concern for governments, energy suppliers, and individual householders. Issues surrounding gas and electricity used in the home relate to the increasing cost of fuel, the rise in the incidence of fuel poverty, carbon dioxide emissions from fossil fuels contributing to climate change, security of supply due to geo-political disagreement and the age and condition of the existing energy infrastructure. While buildings and appliances have become more energy-efficient, usually driven by legislation, the energy-consuming behaviour of individuals is very difficult to change. Domestic energy monitoring has so far only been carried out at a household level, while the behaviour of individuals within households has remained ambiguous. There is a gap in current knowledge about how people use energy at home, mainly because it is very difficult to capture everyday behaviour without influencing the behaviour being observed. Initiatives and campaigns targeting domestic energy-consuming behaviour have been based on assumptions of how people use energy in their homes, and have been found to be ineffective. There is a need for an unobtrusive method of capturing domestic energy behaviour. This research presents a technique to deliver this requirement by enabling the tracking of people in their homes with a small number of cost-effective RFID (Radio Frequency ID) devices. Using this technique the location of multiple individuals wearing RFID tags can be determined, thereby creating an unobtrusive RTLS (Real Time Location System). This technique has been extensively evaluated through a series of tests within a typical 1940’s semi-detached house in North West England, and has been found to be able to successfully locate individuals to room level. If this RTLS data is matched with appliance level energy data, energy-consumption can be attributed to the individuals responsible, and personalised everyday energy-consuming behaviour can be established.
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Atan, Levent. "Multi-Person Infrared Pupil Tracking for 3D TV without Glasses." Thesis, Umeå universitet, Institutionen för informatik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-62822.
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The success of recent 3-D stereoscopic movies such as Avatar has created a lot of attention for 3-D in the home. Almost all major consumer electronics (CE) manufacturers have launched their 3-D stereoscopic displays in the market. A problem with those solutions is that viewers have to wear glasses. Glasses-free autostereoscopic 3-D displays typically use lenticular lenses or barriers to create multiple views. However these displays suffer from a number of issues: inverted views at viewing cone transitions, cross-talk between views, and need for multi-view content. As Philips Electronics research group, we believe that some of these issues can be reduced by using pupil tracking. In the research process, we began with an extensive literature study on people detection and tracking techniques that helped us to understand the benefits and the shortcomings of different applications. Addition to literature studies, we greatly benefited from constant experimentation with prototypes and the hands-on experience with variety of digital and optical components under different conditions. As a result, we designed a multi-person infrared pupil tracker and multi-view renderer for 3D display to adapt the view rendering in real-time according to viewer’s position. Together with the integration of these two applications, the integrated 3D TV successfully adapts the center view according to position of the viewer and able to provide a smooth transition while the viewer actively changes her position from a notable distance under ambient illumination. However, even though the pupil tracker is implemented for multiple people, because of the time limitation and the complexity of the problem regarding multi-view renderer, the integrated system functions only for one person. Exploring the employed technique, in-depth description and detailed illustration of designed applications and the conclusions drawn from the implemented system; we believe that this paper forms a substantial guidance and show-how source for further research in the field of 3D display and people tracking methods.
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Sheehan, Sinéad. "The kinematics of manual pursuit tracking in older adults and stroke patients." Thesis, University of Aberdeen, 2014. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=215169.
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Chapter One justified the need for research into methodology which can examine the upper limb stroke patients and older adults using portable kinematic recording software on the basis of the prevalence of stroke and aging and the potential importance of upper limb impairment as a predictor of recovery from stroke. Chapter Two reviewed the literature on methodologies which measured tracking in stroke patients and found that a wide range of methodologies were available but measurement metrics tended to focus on a small number of indices, mostly root mean square error, suggesting that measuring tracking using other indices might be informative. Chapter Three examined differences in tracking performance between stroke patients and older adults at a range of tracking speeds using a novel kinematic recording technology. The equipment appeared to be feasible for use in a community setting and found that older adults were less accurate, consistent and smooth compared to younger adults, and that accuracy was particularly affected by speed of trial. It was suggested that this interaction between speed and age may have been due to poorer feedback control mechanisms in older adults. Chapter Four looked at stroke patients compared to age-matched controls in tracking performance and found, contrary to the hypothesis, that stroke patients were more accurate, consistent and smooth with both the contralesional and ipsilesional hand; while there was no difference between the hands within stroke patients. Stroke patients may have outperformed controls due to qualitative differences in neural strategies for tracking control or the differences found may have related to methodological differences in collecting data. Chapter Five used the same stroke data to examine the relationship between tracking impairment, activity limitations and participation restrictions within the framework of the International Classification of Functioning, Disability and Health (ICF) (WHO, 2001). It was found that impairment of tracking consistency in the ipsilesional limb predicted participation restriction partially mediated by activity - 5 - limitation. It was argued that tracking in the “unimpaired limb” may be important for predicting participation restriction due to a potential mediating relationship with cognition. The study also suggested that the ipsilesional limb might have potential for rehabilitation of the contralesional limb. Chapter Six discussed the main findings of the thesis. Despite lack of sensitivity of tracking task to stroke impairment, the results of the thesis showed that measuring tracking in older adults and stroke patients provided important information about contralesional and ipsilesional hand function compared to age-matched controls and in relation to activity and participation after stroke. The methodology used may have the potential to examine other research questions which involve the measurement of upper limb kinematics after stroke.
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Mekonnen, Alhayat Ali. "Cooperative people detection and tracking strategies with a mobile robot and wall mounted cameras." Phd thesis, Université Paul Sabatier - Toulouse III, 2014. http://tel.archives-ouvertes.fr/tel-01068355.
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Actuellement, il y a une demande croissante pour le déploiement de robots mobile dans des lieux publics. Pour alimenter cette demande, plusieurs chercheurs ont déployé des systèmes robotiques de prototypes dans des lieux publics comme les hôpitaux, les supermarchés, les musées, et les environnements de bureau. Une principale préoccupation qui ne doit pas être négligé, comme des robots sortent de leur milieu industriel isolé et commencent à interagir avec les humains dans un espace de travail partagé, est une interaction sécuritaire. Pour un robot mobile à avoir un comportement interactif sécuritaire et acceptable - il a besoin de connaître la présence, la localisation et les mouvements de population à mieux comprendre et anticiper leurs intentions et leurs actions. Cette thèse vise à apporter une contribution dans ce sens en mettant l'accent sur les modalités de perception pour détecter et suivre les personnes à proximité d'un robot mobile. Comme une première contribution, cette thèse présente un système automatisé de détection des personnes visuel optimisé qui prend explicitement la demande de calcul prévue sur le robot en considération. Différentes expériences comparatives sont menées pour mettre clairement en évidence les améliorations de ce détecteur apporte à la table, y compris ses effets sur la réactivité du robot lors de missions en ligne. Dans un deuxiè contribution, la thèse propose et valide un cadre de coopération pour fusionner des informations depuis des caméras ambiant affixé au mur et de capteurs montés sur le robot mobile afin de mieux suivre les personnes dans le voisinage. La même structure est également validée par des données de fusion à partir des différents capteurs sur le robot mobile au cours de l'absence de perception externe. Enfin, nous démontrons les améliorations apportées par les modalités perceptives développés en les déployant sur notre plate-forme robotique et illustrant la capacité du robot à percevoir les gens dans les lieux publics supposés et respecter leur espace personnel pendant la navigation.
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Yin, Fei. "Robust wide-area multi-camera tracking of people and vehicles to improve CCTV usage." Thesis, Kingston University, 2011. http://eprints.kingston.ac.uk/20315/.
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This thesis describes work towards a more advanced multiple camera tracking system. This work was sponsored by BARCO who had developed a motion tracker (referred to as the BARCO tracker) and wanted to assess its performance, improve the tracker and explore applications especially for multi-camera systems. The overall requirement then gave rise to specific work in this project: Two trackers (the BARCO tracker and OpenCV 1.0 blobtracker) are tested using a set of datasets with a range of challenges, and their performances are quantitatively evaluated and compared. Then, the BARCO tracker has been further improved by adding three new modules: ghost elimination, shadow removal and improved Kalman filter. Afterwards, the improved tracker is used as part of a multi-camera tracking system. Also, automatic camera calibration methods are proposed to effectively calibrate a network of cameras with minimum manual support (draw lines features in the scene image) and a novel scene modelling method is proposed to overcome the limitations of previous methods. The main contributions of this work to knowledge are listed as follows: A rich set of track based metrics is proposed which allows the user to quantitatively identify specific strengths and weaknesses of an object tracking system, such as the performance of specific modules of the system or failures under specific conditions. Those metrics also allow the user to measure the improvements that have been applied to a tracking system and to compare performance of different tracking methods. For single camera tracking, new modules have been added to the BARCO tracker to improve the tracking performance and prevent specific tracking failures. A novel method is proposed by the author to identify and remove ghost objects. Another two methods are adopted from others to reduce the effect of shadow and improve the accuracy of tracking. For multiple camera tracking, a quick and efficient method is proposed for automatically calibrating multiple cameras into a single view map based on homography mapping. Then, vertical axis based approach is used to fuse detections from single camera views and Kalman filter is employed to track objects on the ground plane. Last but not least, a novel method is proposed to automatically learn a 3D non-coplanar scene model (e.g. multiple levels, stairs, and overpass) by exploiting the variation of pedestrian heights within the scene. Such method will extend the applicability of the existing multi-camera tracking algorithm to a larger variety of environments: both indoors and outdoors where objects (pedestrians and/or vehicles) are not constrained to move on a single flat ground plane.
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Poschmann, Peter. "Multi-sensor multi-person tracking on a mobile robot platform." Doctoral thesis, Technische Universitaet Bergakademie Freiberg Universitaetsbibliothek "Georgius Agricola", 2018. http://nbn-resolving.de/urn:nbn:de:bsz:105-qucosa-235210.
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Service robots need to be aware of persons in their vicinity in order to interact with them. People tracking enables the robot to perceive persons by fusing the information of several sensors. Most robots rely on laser range scanners and RGB cameras for this task. The thesis focuses on the detection and tracking of heads. This allows the robot to establish eye contact, which makes interactions feel more natural.
Developing a fast and reliable pose-invariant head detector is challenging. The head detector that is proposed in this thesis works well on frontal heads, but is not fully pose-invariant. This thesis further explores adaptive tracking to keep track of heads that do not face the robot. Finally, head detector and adaptive tracker are combined within a new people tracking framework and experiments show its effectiveness compared to a state-of-the-art system.
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Bushnell, Megan Haramoto. "The Process of Tracking in Mathematics in Box Elder School District." DigitalCommons@USU, 2008. https://digitalcommons.usu.edu/etd/85.
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Educational policymakers have used tracking to instruct students in a variety of subjects, including mathematics. Tracking, which has also been called ability grouping, is a process by which students in the same grade are placed into different classes based on academic ability. Few educators and sociologists have looked at the process by which students are placed in different mathematics tracks. The research design of this study focused on accumulating, evaluating, and reporting the understanding and observations of 12 teachers and 4 counselors as they discussed their knowledge and involvement in the mathematics placement procedures from the intermediate and middle school levels in northern Utah. The data revealed that in addition to the official placement policies there were other factors that influenced the math placement. Those factors were teacher input, parental participation, and student involvement in the educational process. Educational administration, counselors, and teachers can use the results of this study to create more equitable placement policies and procedures for all students.
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Kräußling, Andreas [Verfasser]. "People-Tracking-Verfahren zur autonomen Identifikation und Begleitung von Personen durch mobile Roboter / Andreas Kräußling." Bonn : Universitäts- und Landesbibliothek Bonn, 2020. http://d-nb.info/1219169277/34.
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Yaneva, Victoria. "Assessing text and web accessibility for people with autism spectrum disorder." Thesis, University of Wolverhampton, 2016. http://hdl.handle.net/2436/620390.
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People with Autism Spectrum Disorder experience difficulties with reading comprehension and information processing, which affect their school performance, employability and social inclusion. The main goal of this work is to investigate new ways to evaluate and improve text and web accessibility for adults with autism. The first stage of this research involved using eye-tracking technology and comprehension testing to collect data from a group of participants with autism and a control group of participants without autism. This series of studies resulted in the development of the ASD corpus, which is the first multimodal corpus of text and gaze data obtained from participants with and without autism. We modelled text complexity and sentence complexity using sets of features matched to the reading difficulties people with autism experience. For document-level classification we trained a readability classifier on a generic corpus with known readability levels (easy, medium and difficult) and then used the ASD corpus to evaluate with unseen user-assessed data. For sentence-level classification, we used for the first time gaze data and comprehension testing to define a gold standard of easy and difficult sentences, which we then used as training and evaluation sets for sentence-level classification. The results showed that both classifiers outperformed other measures of complexity and were more accurate predictors of the comprehension of people with autism. We conducted a series of experiments evaluating easy-to-read documents for people with cognitive disabilities. Easy-to-read documents are written in an accessible way, following specific writing guidelines and containing both text and images. We focused mainly on the image component of these documents, a topic which has been significantly under-studied compared to the text component; we were also motivated by the fact that people with autism are very strong visual thinkers and that therefore image insertion could be a way to use their strengths in visual thinking to compensate for their difficulties in reading. We investigated the effects images in text have on attention, comprehension, memorisation and user preferences in people with autism (all of these phenomena were investigated both objectively and subjectively). The results of these experiments were synthesised in a set of guidelines for improving text accessibility for people with autism. Finally, we evaluated the accessibility of web pages with different levels of visual complexity. We provide evidence of existing barriers to finding relevant information on web pages that people with autism face and we explore their subjective experiences with searching the web through survey questions.
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Danezis, C. "Assessment of the ability of digital terrain models to aid GPS tracking of people and animals." Thesis, University College London (University of London), 2011. http://discovery.ucl.ac.uk/1331877/.
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The advent of global navigation satellite systems, and especially GPS, signified a new era in navigation. Although GPS tends to be a panacea in terms of positioning and tracking, there are still cases whereby severe problems can render navigation virtually impossible. Difficult GNSS environments such as forests, heavy canopy covered areas, or urban canyons can have a negative impact on the propagation of satellite signal and introduce large errors in positioning due to signal attenuation. Several techniques have been developed to deal with this issue, e.g. integrated GNSS/INS navigation configurations. This thesis focuses on the application of terrain aiding and its impact on the availability, accuracy, and reliability of GNSS positioning. Furthermore, it examines the impact of using GNSS receivers of different grade and different chipset sensitivity in such operations. Two main experiments were carried out; the first was conducted in the mountains of Transylvania, in Romania. This project was sponsored by the European GNSS supervisory authority, and involved the tracking of animals (bears in this case). The second experiment was held in Greenwich Park, London, using an accurate terrain model, kindly provided by the Ordnance Survey of Great Britain. In both cases, new algorithms have been developed to combine satellite tracking with local terrain models to improve positioning performance. The results indicate that in the case of standard sensitivity receivers the use of an accurate digital terrain model can improve positioning availability by as much as 74%, and the accuracy of normal four-satellite positioning by a factor of up to five. Furthermore, it was found that, for both standard and high sensitivity receivers, the external reliability of position fixes can be improved by an average of 40%, and up to 90% in some cases.
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Kenemer, John B. "An Evaluation of the State Tobacco Activities Tracking and Evaluation (STATE) System: Cross-Promoting Healthy People 2020." Digital Archive @ GSU, 2012. http://digitalarchive.gsu.edu/iph_theses/235.
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The State Tobacco Activities Tracking and Evaluation (STATE) System is an interactive web-based application and data tool providing up-to-date state-level information related to tobacco use. Indicators in STATE present data related to current and former tobacco use, smoking cessation, funding, tobacco-related health costs, and tobacco control policies. The STATE System also serves as a primary data source for many objectives in Healthy People 2020’s Tobacco Use chapter. Currently, there is no common thread between access to information pertaining to Healthy People 2020 objectives and STATE System data. For this reason, a comprehensive evaluation was conducted of the STATE System’s individual reports and static web-content as it relates to Healthy People 2020 objectives. Implications for research and evaluation are intended to educate the Office on Smoking and Health’s staff & colleagues in the states, networks, and territories on identifiable, cross-promotional opportunities that highlight both state and national data.
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Conte, Donatello Jolion Jean-Michel Vento Mario. "Detection, tracking, and behaviour analysis of moving people in intelligent video surveillance systems a graph based approach /." Villeurbanne : Doc'INSA, 2006. http://docinsa.insa-lyon.fr/these/pont.php?id=conte.
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Conte, Donatello. "Detection, tracking, and behaviour analysis of moving people in intelligent video surveillance systems : a graph based approach." Lyon, INSA, 2006. http://theses.insa-lyon.fr/publication/2006ISAL0033/these.pdf.
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In this thesis video surveillance system is proposed. For each step of such systems it presents some innovations as regard as the state of the art in such systems. First of all, a new selectively and adaptively background substraction algorithm has been proposed to adapt the system at illumination and scene changes. Furthermore, some heuristics are proposed to solve object detection problems in real environment shadows, noise, etc. Result show that proposed techniques are robust in terms of quality of solution and, besides, they are efficient in terms of processing time. The main object of the thesis concerns the object tracking phase. In the thesis we propose a new algorithm based on a new representation of the objects : the graph pyramids. This presentation allows the resolutions of occlusions also in complex cases. They are preformed on standard datasets and standard indexes to provide objective results. The results show the approch is promisingDans cette thèse, nous proposons un système de vidéo surveillance qui présente des nouveaux algorithmes de détection d’objets et de suivi d’objets, afin de pallier les principaux problèmes qui se présentent dans le développement de tels systèmes. Il a été proposé un nouvel algorithme de soustraction du fond, sélectif et adaptatif, pour adapter le système à des changements de luminosité et de la structure de la scène. En outre, pour rendre applicable le système à des environnements réels, des heuristiques ont été proposées pour la résolution des différents problèmes : ombres, bruit, etc. Les résultats produits sur la phase de détection d’objets montrent que les techniques proposées sont robustes et utilisables en temps réels grâce à un temps de calcul peu élevé. L’objet principal de la thèse a concerné la phase de suivi d’objets. Dans cette thèse, nous proposons un nouvel algorithme basé sur une expérimentation des objets qui utilisent les pyramides de graphes. Des tests expérimentaux sur des bases de données standard et sur des index attestés pour l’évaluation des algorithmes de suivi d’objets en présence d’occlusions montrent que cette approche est très prometteuse
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Nguyen, Thi Lan Anh. "Suivi long terme de personnes pour les systèmes de vidéo monitoring." Thesis, Université Côte d'Azur (ComUE), 2018. http://www.theses.fr/2018AZUR4053/document.
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Le suivi d'objets multiples (Multiple Object Tracking (MOT)) est une tâche importante dans le domaine de la vision par ordinateur. Plusieurs facteurs tels que les occlusions, l'éclairage et les densités d'objets restent des problèmes ouverts pour le MOT. Par conséquent, cette thèse propose trois approches MOT qui se distinguent à travers deux propriétés : leur généralité et leur efficacité.La première approche sélectionne automatiquement les primitives visions les plus fiables pour caractériser chaque tracklet dans une scène vidéo. Aucun processus d’apprentissage n'est nécessaire, ce qui rend cet algorithme générique et déployable pour une grande variété de systèmes de suivi.La seconde méthode règle les paramètres de suivi en ligne pour chaque tracklet, en fonction de la variation du contexte qui l’entoure. Il n'y a pas de contraintes sur le nombre de paramètres de suivi et sur leur dépendance mutuelle. Cependant, on a besoin de données d'apprentissage suffisamment représentatives pour rendre cet algorithme générique.La troisième approche tire pleinement avantage des primitives visions (définies manuellement ou apprises), et des métriques définies sur les tracklets, proposées pour la ré-identification et leur adaptation au MOT. L’approche peut fonctionner avec ou sans étape d'apprentissage en fonction de la métrique utilisée.Les expériences sur trois ensembles de vidéos, MOT2015, MOT2017 et ParkingLot montrent que la troisième approche est la plus efficace. L'algorithme MOT le plus approprié peut être sélectionné, en fonction de l'application choisie et de la disponibilité de l’ensemble des données d'apprentissageMultiple Object Tracking (MOT) is an important computer vision task and many MOT issues are still unsolved. Factors such as occlusions, illumination, object densities are big challenges for MOT. Therefore, this thesis proposes three MOT approaches to handle these challenges. The proposed approaches can be distinguished through two properties: their generality and their effectiveness.The first approach selects automatically the most reliable features to characterize each tracklet in a video scene. No training process is needed which makes this algorithm generic and deployable within a large variety of tracking frameworks. The second method tunes online tracking parameters for each tracklet according to the variation of the tracklet's surrounding context. There is no requirement on the number of tunable tracking parameters as well as their mutual dependence in the learning process. However, there is a need of training data which should be representative enough to make this algorithm generic. The third approach takes full advantage of features (hand-crafted and learned features) and tracklet affinity measurements proposed for the Re-id task and adapting them to MOT. Framework can work with or without training step depending on the tracklet affinity measurement.The experiments over three datasets, MOT2015, MOT2017 and ParkingLot show that the third approach is the most effective. The first and the third (without training) approaches are the most generic while the third approach (with training) necessitates the most supervision. Therefore, depending on the application as well as the availability of a training dataset, the most appropriate MOT algorithm could be selected
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Byrne, Ceara Ann. "Design of an e-Textile sleeve for tracking knee rehabilitation for older adults." Thesis, Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/49047.
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The occurrence of total knee replacements is increasing in the United States for persons over the age of 45 because they are inexpensive and a very effective method for treating degenerative joint diseases. Rehabilitation requires regular access to a wide variety of resources and personnel and, as the demand for post-operative, rehabilitative care increases, the ability to marginally relieve the healthcare system by offloading resources to the patient is necessary. Tools to enable tracking a patient’s rehabilitative progress at home are an essential method to help unload the healthcare system. The purpose of this project is to design and develop a wearable home rehabilitation device for knee replacement. This thesis utilizes design ethnography tools such as expert interviews, rehabilitation observation, a participatory design workshop, iterative development, and an idea feedback study. Leveraging advancements in technology and the field of eTextiles, this study investigates the product feasibility and acceptance of discreet on-body sensors to provide a product that enables patients to better perform rehabilitation on their own, but also to allow for a feedback loop for physicians and therapists to view patient progress.
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Gasperini, Stefano. "A travel-guidance engine for visually impaired people." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/11650/.
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Fino a pochi anni fa, usare i trasporti pubblici poteva essere fonte di confusione e richiedere la comprensione del sistema dei trasporti locali. Più tardi, con la diffusione di dispositivi con localizzazione GPS, reti dati cellulare e Google Maps (inizialmente Google Transit), tutto è cambiato, rendendo possibile la pianificazione di un viaggio mentre si è fuori casa. Nonostante Google Maps disponga di indicazioni stradali più o meno in tutto il mondo e mostri molte informazioni, alcune funzionalità, come l’integrazione degli orari in tempo reale, non sono disponibili in tutte le città, ma sono basate su accordi con le agenzie dei trasporti locali.
GoGoBus è un’applicazione Android per l’ausilio al trasporto nella città di Bologna. Combinando diversi servizi, GoGoBus si rivolge a svariati tipi di utilizzatori: offre la pianificazione per i meno pratici del sistema e coloro che usano i trasporti pubblici raramente, dispone di orari in tempo reale per chi usa i mezzi frequentemente, e in più traccia la posizione dell’autobus, ha un supporto vocale e un’interfaccia semplice per persone con disabilità. Progettata appositamente per ipovedenti, l’aspetto più innovativo dell’applicazione è il suo supporto durante il percorso sull’autobus, integrato alla pianificazione del tragitto e agli orari aggiornati in tempo reale. Il sistema traccia la posizione dell’autobus attraverso il GPS del dispositivo mobile, la cui posizione è usata sia per riconoscere quando una fermata viene superata, sia per mostrare informazioni utili come la distanza dalla prossima fermata, il numero di fermate e i minuti rimanenti prima di scendere, e soprattutto notificare l’utente quando deve scendere. L’idea dietro GoGoBus è incrementare la fruibilità dei trasporti pubblici per non vedenti, ma anche per persone che li usano di rado, aumentando ampiamente la loro indipendenza, allo stesso tempo migliorando la qualità del servizio per chi usa i mezzi quotidianamente.
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Jovanoska, Snezhana [Verfasser], Reiner [Akademischer Betreuer] Thomä, Wolfgang [Gutachter] Koch, and Dirk [Gutachter] Heberling. "Localisation and tracking of people using distributed UWB sensors / Snezhana Jovanoska ; Gutachter: Wolfgang Koch, Dirk Heberling ; Betreuer: Reiner Thomä." Ilmenau : TU Ilmenau, 2020. http://d-nb.info/1216038945/34.
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Rello, Luz. "DysWebxia : a text accessibility model for people with dyslexia." Doctoral thesis, Universitat Pompeu Fabra, 2014. http://hdl.handle.net/10803/283113.
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Worldwide, 10% of the population has dyslexia, a cognitive disability that reduces readability and comprehension of written information. The goal of this thesis is to make text more accessible for people with dyslexia by combining human computer interaction validation methods and natural language processing techniques. In the initial phase of this study we examined how people with dyslexia identify errors in written text. Their written errors were analyzed and used to estimate the presence of text written by individuals with dyslexia in the Web. After concluding that dyslexic errors relate to presentation and content features of text, we carried out a set of experiments using eye tracking to determine the conditions that led to improved readability and comprehension. After finding the relevant parameters for text presentation and content modification, we implemented a lexical simplification system. Finally, the results of the investigation and the resources created, lead to a model, DysWebxia, that proposes a set of recommendations that have been successfully integrated in four applications.Un 10% de la població mundial té dislèxia, una dificultat cognitiva que redueix la llegibilitat i la comprensió de la informació escrita. L’objectiu de la tesiés millorar l’accessibilitat textual de les persones amb dislèxia, combinant mètodes de validació de la interacció persona-ordinador i tècniques de processament del llenguatge natural. Vam estudiar com identifiquen els errors d’un text les persones amb dislèxia i vam analitzar els seus errors d’escriptura; això va servir per a estimar la presència a la web de textos escrits per persones amb dislèxia. Un cop establert que els errors dislèctics responen a trets relacionats amb la presentació i el contingut del text, vam realitzar experiments mitjan ̧cant el seguiment de la mirada per a descobrir quines condicions milloren la llegibilitat i la comprensió. Havent determinat els paràmetres rellevants per a la presentació del text i la modificació dels continguts, vam implementar un sistema de simplificació lèxica. Els resultats obtinguts i els recursos creats han donat lloc a un model, DysWebxia, en el qual es proposen recomanacions que s’han integrat satisfacto`riament en quatre aplicacions.
Un 10% de la población mundial tiene dislexia, una dificultad de aprendizaje de origen cognitivo que reduce la legibilidad y la comprensión de la información escrita. El objetivo de esta tesis es mejorar la accesibilidad textual de las personas con dislexia, combinando métodos de validación de interacción persona-ordenador y técnicas de procesamiento del lenguaje natural. Primero estudiamos como las personas con dislexia identifican los errores en un texto y analizamos sus errores escritos. Esto permitió estimar la presencia en la Web de textos escritos por personas con dislexia. Al descubrir que los errores disléxicos están relacionados tanto con la presentación como con el contenido del texto, llevamos a cabo una serie de experimentos utilizando seguimiento automático de la vista (eye tracking) para averiguar qué condiciones mejoraban la legibilidad y la comprensión. Después de determinar los parámetros relevantes para la presentación del texto y la modificación de su contenido, implementamos un sistema de simplificación léxica. Los resultados obtenidos y los recursos generados han dado lugar a un modelo, DysWebxia, que propone recomendaciones que ya han sido integradas satisfactoriamente en cuatro aplicaciones.
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Chen, Lili [Verfasser], Alois [Akademischer Betreuer] Knoll, and Rüdiger [Akademischer Betreuer] Dillmann. "Multiple People Tracking-by-Detection in a Multi-camera Environment / Lili Chen. Gutachter: Rüdiger Dillmann ; Alois Knoll. Betreuer: Alois Knoll." München : Universitätsbibliothek der TU München, 2015. http://d-nb.info/1065804121/34.
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Andriluka, Mykhaylo [Verfasser], Stefan [Akademischer Betreuer] Roth, Daniel [Akademischer Betreuer] Huttenlocher, and Bernt [Akademischer Betreuer] Schiele. "Detection, Tracking and Pose Estimation of People in Challenging Real-World Scenes / Mykhaylo Andriluka. Betreuer: Stefan Roth ; Daniel Huttenlocher ; Bernt Schiele." Darmstadt : Universitäts- und Landesbibliothek Darmstadt, 2011. http://d-nb.info/1105564010/34.
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Bazar, Nancy Sceery. "Web usability or accessibility comparisons between people with and without intellectual disabilities in viewing complex naturalistic scenes using eye-tracking technology /." Fairfax, VA : George Mason University, 2009. http://hdl.handle.net/1920/4559.
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Thesis (Ph.D.)--George Mason University, 2009.Vita: p. 238. Thesis director: Frederick Brigham. Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Education. Title from PDF t.p. (viewed Oct. 12, 2009). Includes bibliographical references (p. 229-237). Also issued in print.
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Badie, Julien. "Optimisation du suivi de personnes dans un réseau de caméras." Thesis, Nice, 2015. http://www.theses.fr/2015NICE4090/document.
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Cette thèse s’intéresse à l’amélioration des performances du processus de suivi de personnes dans un réseau de caméras et propose une nouvelle plate-forme appelée global tracker. Cette plate-forme évalue la qualité des trajectoires obtenues par un simple algorithme de suivi et permet de corriger les erreurs potentielles de cette première étape de suivi. La première partie de ce global tracker estime la qualité des trajectoires à partir d’un modèle statistique analysant des distributions des caractéristiques de la cible (ie : l’objet suivi) telles que ses dimensions, sa vitesse, sa direction, afin de détecter de potentielles anomalies. Pour distinguer de véritables erreurs par rapport à des phénomènes optiques, nous analysons toutes les interactions entre l’objet suivi et tout son environnement incluant d’autres objets mobiles et les éléments du fond de la scène. Dans la deuxième partie du global tracker, une méthode en post-traitement a été conçue pour associer les différentes tracklets (ie : segments de trajectoires fiables) correspondant à la même personne qui n’auraient pas été associées correctement par la première étape de suivi. L’algorithme d’association des tracklets choisit les caractéristiques d’apparence les plus saillantes et discriminantes afin de calculer une signature visuelle adaptée à chaque tracklet. Finalement le global tracker est évalué à partir de plusieurs bases de données de benchmark qui reproduit une large variété de situations réelles. A travers toutes ces expérimentations, les performances du global tracker sont équivalentes ou supérieures aux meilleurs algorithmes de suivi de l’état de l’artThis thesis addresses the problem of improving the performance of people tracking process in a new framework called Global Tracker, which evaluates the quality of people trajectory (obtained by simple tracker) and recovers the potential errors from the previous stage. The first part of this Global Tracker estimates the quality of the tracking results, based on a statistical model analyzing the distribution of the target features to detect potential anomalies.To differentiate real errors from natural phenomena, we analyze all the interactions between the tracked object and its surroundings (other objects and background elements). In the second part, a post tracking method is designed to associate different tracklets (segments of trajectory) corresponding to the same person which were not associated by a first stage of tracking. This tracklet matching process selects the most relevant appearance features to compute a visual signature for each tracklet. Finally, the Global Tracker is evaluated with various benchmark datasets reproducing real-life situations, outperforming the state-of-the-art trackers
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Kundu, Rupam. "A Single Camera based Localization and Navigation Assistance for The Visually Impaired in Indoor Environments." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu154593040067708.
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Černín, Jan. "Vizuální detekce osob v komerčních aplikacích." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219704.
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The aim of the master thesis is to derive and implement image porcessing methods for people detection and tracking in images or videos. The overall solution was chosen as a combination of modern approaches and methods which were recently presented. The proposed algorithm is able to create trajectory of the person moving in indoor building spaces even under influence of full or partial occlusion for a short period of time. The scene of interest is surveyed by a static camera having direct view on targets. Selected methods are implemented in C# programming language based on OpenCV library. Graphical user interface was created to show the final output of algorithm.
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Burbano, Andres. "Système de caméras intelligentes pour l’étude en temps-réel de personnes en mouvement." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLS139/document.
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Nous proposons un système dedétection et de suivi des personnes enmouvement dans des grands espaces. Notresolution repose sur un réseau de camérasintelligentes pour l'extraction desinformations spatio-temporelles despersonnes. Les caméras sont composées d'uncapteur 3D, d'un système embarqué et decommunication. Nous avons montrél'efficacité du placement des capteurs 3D enposition zénithale par rapport auxoccultations et variations d’échelle.Nous garantissons l'exécution des traitementsen temps-réel (~20 fps), permettantde détecter des déplacements rapides avecune précision jusqu’à 99 %, et capable d’unfiltrage paramétrique des cibles non désiréescomme les enfants ou les caddies.Nous avons réalisé une étude sur la viabilitétechnologique des résultats pour de grandsespaces, rendant la solution industrialisableWe propose a detection and trackingsystem of people moving in large spacessystem. Our solution is based on a network ofsmart cameras capable of retrievingspatiotemporal information from the observedpeople. These smart cameras are composed bya 3d sensor, an onboard system and acommunication and power supply system. Weexposed the efficacy of the overhead positionto decreasing the occlusion and the scale'svariation.Finally, we carried out a study on the use ofspace, and a global trajectories analysis ofrecovered information by our and otherssystems, able to track people in large andcomplex spaces
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Bartl, Vojtěch. "Mapování pohybu osob stacionární kamerou." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2015. http://www.nusl.cz/ntk/nusl-235002.
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The aim of this diploma thesis is to obtain information on the motion of people in a scene from the record of the stationary camera. The procedure to detect exceptional events in the scene was designed. Exceptional events can be fast-moving persons, or persons moving in di erent places than everyone else in the scene. To trace the motion of persons, two algorithms were applied and tested - Optical flow and CAMSHIFT. The analysis of the resulting motions is performed by monitoring the progress of motion, and its comparison with the other motions in the scene. The analysis result is represented by detected exceptional motions that can be found in the video. The areas where the motion occurs in the scene, and where the motion is the most common are also described together with the motion direction analysis. The exceptional motion parts extracted from the video represent the main result of the work.