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Analysis of Visual Distinctive Features for the Global Tracking of Multiple Objects

Götz, Matthias (2012)
Analysis of Visual Distinctive Features for the Global Tracking of Multiple Objects.
Technische Universität Darmstadt
Masterarbeit, Bibliographie

Kurzbeschreibung (Abstract)

Tracking has many possible applications as in surveillance systems, robot vision, automotive safety and so on. Therefore tracking of multiple targets in image sequences has become a classical task in computer vision. An example for an application is the use in driver assistance systems to avoid collisions. In this work a multi-target tracking framework which formulates multi-target tracking as minimization of a continuous energy function and solves minimization by conjugate gradient method with periodic trans-dimensional jumps is extended by an appearance-based energy term. Other than a number of recent approaches not only an appearance model consisting of a descriptor and a metric is selected. Instead many other possibilities such as weighting, prefilter and so on are considered. A couple of visual distinctive features with their parameters are optimized by random search and analyzed to find a good appearance model for the integration in the framework. The extension of the multi-target tracking framework is evaluated in experiments on two image sequences with variation in the influence of the new energy term. The addition of the appearance-based energy term leads to an increase in the performance of the tracking results.

Typ des Eintrags: Masterarbeit
Erschienen: 2012
Autor(en): Götz, Matthias
Art des Eintrags: Bibliographie
Titel: Analysis of Visual Distinctive Features for the Global Tracking of Multiple Objects
Sprache: Englisch
Publikationsjahr: 2012
Ort: Darmstadt
Kurzbeschreibung (Abstract):

Tracking has many possible applications as in surveillance systems, robot vision, automotive safety and so on. Therefore tracking of multiple targets in image sequences has become a classical task in computer vision. An example for an application is the use in driver assistance systems to avoid collisions. In this work a multi-target tracking framework which formulates multi-target tracking as minimization of a continuous energy function and solves minimization by conjugate gradient method with periodic trans-dimensional jumps is extended by an appearance-based energy term. Other than a number of recent approaches not only an appearance model consisting of a descriptor and a metric is selected. Instead many other possibilities such as weighting, prefilter and so on are considered. A couple of visual distinctive features with their parameters are optimized by random search and analyzed to find a good appearance model for the integration in the framework. The extension of the multi-target tracking framework is evaluated in experiments on two image sequences with variation in the influence of the new energy term. The addition of the appearance-based energy term leads to an increase in the performance of the tracking results.

Freie Schlagworte: Computer vision, Tracking, Computer vision based tracking, 3D Tracking, Camera tracking, People tracking, Active appearance models
Zusätzliche Informationen:

92 p.

Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Graphisch-Interaktive Systeme
Hinterlegungsdatum: 12 Nov 2018 11:16
Letzte Änderung: 07 Dez 2023 07:04
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