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Multiple Object Tracking by Scale Space Representation of Objects, Method of Linear Assignment, and Kalman Filter

Multiple Object Tracking by Scale Space Representation of Objects, Method of Linear Assignment, and Kalman Filter
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Author(s): Kumar S. Ray (Indian Statistical Institute, India), Soma Ghosh (Indian Statistical Institute, India), Kingshuk Chatterjee (Indian Statistical Institute, India)and Debayan Ganguly (Indian Statistical Institute, India)
Copyright: 2018
Pages: 24
Source title: Computer Vision: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-5204-8.ch032

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Abstract

This chapter presents a multi-object tracking system using scale space representation of objects, the method of linear assignment and Kalman filter. In this chapter basically two very prominent problems of multi object tracking have been resolved; the two prominent problems are (i) irrespective of the size of the objects, tracking all the moving objects simultaneously and (ii) tracking of objects under partial and/or complete occlusion. The primary task of tracking multiple objects is performed by the method of linear assignment for which few cost parameters are computed depending upon the extracted features of moving objects in video scene. In the feature extraction phase scale space representation of objects have been used. Tracking of occluded objects is performed by Kalman filter.

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