期刊论文

Ou, Weihua

英文

Journal of Electronic Imaging

1017-9909

2017

26

3

033006

10.1117/1.JEI.26.3.033006

This work was supported by the the National Natural Science Foundation of China (Nos. 61402122, 61672183, and 61272252), Science and Technology Planning Project of Guanddong Province (Grant No. 2016B090918047), Natural Science Foundation of Guangdong Province (Grant No. 2015A030313544), Shenzhen Research Council (Grant Nos. JCYJ20160406161948211, JCYJ20160226201453085, and JSGG20150331152017052), and the 2014 PhD Recruitment ProgramofGuizhou Normal University, the Outstanding Innovation Talents of Science and Technology Award Scheme of Education Department in Guizhou Province (Qian jiao KY word[2015]487), Natural Science Foundation of Guizhou (LH[2015]7784), the China Scholarship Council (No. 201508525007), and Fund of Guizhou Educational Department (KY[2016]027). No conflicts.

本校为其他机构

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...