Relevant bibliographies by topics / Detection and tracking pedestrians

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  1. Dissertations / Theses

Academic literature on the topic 'Detection and tracking pedestrians'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 February 2022

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Dissertations / Theses on the topic "Detection and tracking pedestrians"

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Suppitaksakul, Chatchai. "Pedestrian detection and tracking." Thesis, Northumbria University, 2006. http://nrl.northumbria.ac.uk/488/.

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This report presents work on the detection and tracking of people in digital images. The employed detection technique is based on image processing and classification techniques. The work uses an object detection process to detect object candidate locations and a classification method using a Self-Organising Map neural network to identify the pedestrian head positions in an image. The proposed tracking technique with the support of a novel prediction method is based on the association of Cellular Automata (CA) and a Backpropagation Neural Network (BPNN). The tracking employs the CA to capture t
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Tabb, Ken John. "Detecting and tracking pedestrians using active contour models and neural networks." Thesis, University of Hertfordshire, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.421260.

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Hasfura, Andrés Michael Levering. "Pedestrian detection and tracking for mobility on demand." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/106011.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 69-72).<br>This paper presents a pedestrian detection and tracking system to be used aboard mobility on demand systems. Mobility on demand is a transportation paradigm in which a fleet of vehicles is shared among a community
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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
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Zuo, Tianyu. "An Efficient Vision-Based Pedestrian Detection and Tracking System for ITS Applications." Thesis, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31778.

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In this thesis, a novel Pedestrian Protection System (PPS), composed of the Pedestrian Detection System (PDS) and the Pedestrian Tracking System (PTS), was proposed. The PPS is a supplementary application for the Advanced Driver Assistance System, which is used to avoid collisions between vehicles and pedestrians. The Pedestrian Detection System (PDS) is used to detect pedestrians from near to far ranges with the feature-classi er-based detection method (HOG + SVM). To achieve pedestrian detection from near to far ranges, a novel structure was proposed. The structure of our PDS consi
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Peng, Zeng. "Pedestrian Tracking by using Deep Neural Networks." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-302107.

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This project aims at using deep learning to solve the pedestrian tracking problem for Autonomous driving usage. The research area is in the domain of computer vision and deep learning. Multi-Object Tracking (MOT) aims at tracking multiple targets simultaneously in a video data. The main application scenarios of MOT are security monitoring and autonomous driving. In these scenarios, we often need to track many targets at the same time which is not possible with only object detection or single object tracking algorithms for their lack of stability and usability. Therefore we need to explore the
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Reilly, Vladimir. "Detecting, Tracking, and Recognizing Activities in Aerial Video." Doctoral diss., University of Central Florida, 2012. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5454.

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In this dissertation we address the problem of detecting humans and vehicles, tracking their identities in crowded scenes, and finally determining human activities. First, we tackle the problem of detecting moving as well as stationary objects in scenes that contain parallax and shadows. We constrain the search of pedestrians and vehicles by representing them as shadow casting out of plane or (SCOOP) objects. Next, we propose a novel method for tracking a large number of densely moving objects in aerial video. We divide the scene into grid cells to define a set of local scene constraints w
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Eiselein, Volker [Verfasser], Thomas [Akademischer Betreuer] Sikora, Thomas [Gutachter] Sikora, Olaf [Gutachter] Hellwich, and Jian [Gutachter] Zhang. "Pedestrian tracking-by-detection for video surveillance applications / Volker Eiselein ; Gutachter: Thomas Sikora, Olaf Hellwich, Jian Zhang ; Betreuer: Thomas Sikora." Berlin : Technische Universität Berlin, 2019. http://d-nb.info/1200991249/34.

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Adiaviakoye, Ladji. "Observatoire de trajectoire de piétons à l'aide d'un réseau de télémètre laser à balayage : application à l'intérieur des bâtiments." Thesis, Angers, 2015. http://www.theses.fr/2015ANGE0086.

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Dans la vie de tous les jours, nous assistons à des chorégraphies surprenantes dans les déplacements de foules de piétons. Les mécanismes qui sont à la base de la dynamique des foules humaines restent peu connus. Un des modes d’observation des piétons consiste à réaliser des mesures en conditions réelles (exemple : aéroport, gare, etc.). La trajectoire empruntée, la vitesse et l’accélération sont les données de base pour une telle analyse. C’est dans ce contexte que se placent nos travaux qui combinent étroitement observations en milieu naturel et expérimentations contrôlées. Nous avons propos
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Jerrelind, Jakob. "Tracking of Pedestrians Using Multi-Target Tracking Methods with a Group Representation." Thesis, Linköpings universitet, Reglerteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-172579.

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Multi-target tracking (MTT) methods estimate the trajectory of targets from noisy measurement; therefore, they can be used to handle the pedestrian-vehicle interaction for a moving vehicle. MTT has an important part in assisting the Automated Driving System and the Advanced Driving Assistance System to avoid pedestrian-vehicle collisions. ADAS and ADS rely on correct estimates of the pedestrians' position and velocity, to avoid collisions or unnecessary emergency breaking of the vehicle. Therefore, to help the risk evaluation in these systems, the MTT needs to provide accurate and robust infor
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