Non-symmetry and Anti-packing Pattern Representation Model in Visual Tracking
Based on the non-symmetry and anti-packing pattern representation model (NAM), we propose a new division model in object tracking, whose most important characteristic is asymmetry. For the target region, we divide it into homogeneous blocks of different sizes and irregular positions. Pixels in the same homogeneous block have similar values, so we can use mean value and area to represent the feature of this block. When tracking the object, the proposed algorithm updates the mean values of each block to adapt to the change of the object. The characteristics of the whole target consist of the feature information and the position information of each block. Compared with the traditional division models, the NAM has fewer divided blocks but more highlight target structure characteristics. The experimental results in this paper show that our proposed tracking algorithm based on the NAM is better than those based on the quadtree or the compression tracking (CT) in both accuracy and speed.
KeywordsVisual tracking NAM Quadtree Compression tracking
This work is supported by the National Natural Science Foundation of China under Grant No. 61300134, the Research Fund for the Doctoral Program of Higher Education of China under Grant No. 20120172120036, the Natural Science Foundation of Guangdong Province of China under Grant No. S2011040005815, No. S2013010012515, No. 2015A030313206, and No. 2017A030313349, the Fundamental Research Funds for the Central Universities of China under Grant No. 2015ZM133, the Chinese National Scholarship Fund under Grant No. 201406155015, and the Undergraduate Innovative and Entrepreneurial Training Program of Guangdong Province of China under Grant No. S201910561235.
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