Dr. Di Yuan Profile

Dr. Di Yuan

at HIT Shenzhen Graduate School

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SPIE Journal Paper | 13 May 2017

Patch-based visual tracking with online representative sample selection

Weihua Ou, Di Yuan, Donghao Li, Bin Liu, Daoxun Xia, Wu Zeng

JEI, Vol. 26, Issue 03, 033006, (May 2017) https://doi.org/10.1117/12.10.1117/1.JEI.26.3.033006

KEYWORDS: Optical tracking, Visualization, Lead

Read Abstract +

Occlusion is one of the most challenging problems in visual object tracking. Recently, a lot of discriminative methods have been proposed to deal with this problem. For the discriminative methods, it is difficult to select the representative samples for the target template updating. In general, the holistic bounding boxes that contain tracked results are selected as the positive samples. However, when the objects are occluded, this simple strategy easily introduces the noises into the training data set and the target template and then leads the tracker to drift away from the target seriously. To address this problem, we propose a robust patch-based visual tracker with online representative sample selection. Different from previous works, we divide the object and the candidates into several patches uniformly and propose a score function to calculate the score of each patch independently. Then, the average score is adopted to determine the optimal candidate. Finally, we utilize the non-negative least square method to find the representative samples, which are used to update the target template. The experimental results on the object tracking benchmark 2013 and on the 13 challenging sequences show that the proposed method is robust to the occlusion and achieves promising results.

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