Real-time multi-target tracking: A study on color-texture covariance matrices and descriptor/operator switching (original) (raw)

Abstract

This thesis proposes a computer vision system for detecting and tracking multiple targets in videos. The covariance matching method is the guiding thread of our work because it offers a compact representation of the target by embedding heterogeneous features in a elegant way. Therefore, it is efficient both for tracking and recognition. Four categories of contributions are proposed. The first one deals with the adaptation to a changing context, following two aspects. A preliminary work consists in the adaptation of color according to lighting variations and relevance of the color. Then, literature shows a wide variety of tracking methods, which have both advantages and limitations, depending on the object to track and the context. Here, a deterministic method is developed to automatically adapt the tracking method to the context through the cooperation of two complementary techniques. A first proposition combines covariance matching for modeling characteristics texture-color informa...

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