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In this paper we tackle the challenges of visual tracking for personal robots. We have proposed a novel track-by-detection method that combines a semantic object model with depth properties to obtain target contours. The tracking can be initialized by either 2D or 3D inputs, which are further refined using clustering based background removal to obtain an initial object model. During tracking, we propose...
Distributed processing is a new paradigm to analyse the huge volume of video data in camera networks. This paper addresses the problem of distributed single target tracking considering false positives and missed detections. Target tracking is modelled as a dynamic state estimation problem with nonlinear process and measurement model. We propose to use the sigma point information filters combined with...
Using color information in object tracking is a prudent choice, but the vast variety of choices and difficulties of obtaining a desirable stable result, unnerves many scholars. Color histograms, as a compact and robust representation is the center of attention while it suffers from lack of spatial information about colors. Besides, comparison and updating such histograms in a meaningful and efficient...
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