Fast tracking based on local histogram of oriented gradient and dual detection

Huan Shi; Kai; Fei Cheng; Wenwen Ding; Baijian Zhang

doi:10.1117/12.2223625

12 May 2016 Fast tracking based on local histogram of oriented gradient and dual detection

Huan Shi, Kai, Fei Cheng, Wenwen Ding, Baijian Zhang

Proceedings Volume 9844, Automatic Target Recognition XXVI; 98440Q (2016) https://doi.org/10.1117/12.2223625
Event: SPIE Defense + Security, 2016, Baltimore, MD, United States

Abstract

Visual tracking is important in computer vision. At present, although many algorithms of visual tracking have been proposed, there are still many problems which are needed to be solved, such as occlusion and frame speed. To solve these problems, this paper proposes a novel method which based on compressive tracking. Firstly, we make sure the occlusion happens if the testing result about image features by the classifiers is lower than a threshold value which is certain. Secondly, we mark the occluded image and record the occlusion region. In the next frame, we test both the classifier and the marked image. This algorithm makes sure the tracking is fast, and the result about solving occlusion is much better than other algorithms, especially compressive tracking.

Citation Download Citation

Huan Shi, Kai, Fei Cheng, Wenwen Ding, and Baijian Zhang "Fast tracking based on local histogram of oriented gradient and dual detection", Proc. SPIE 9844, Automatic Target Recognition XXVI, 98440Q (12 May 2016); https://doi.org/10.1117/12.2223625

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