DocumentCode :
3680986
Title :
Adaptive Real-Time Compressive Tracking
Author :
Wei-Zheng Zhang;Jian-Guo Ji;Zhong-Zhao Jing;Wen-Feng Jing;Yi Zhang
Author_Institution :
Zheng zhou Power Supply Co., State Grid Henan Electr. Power Co., Zhengzhou, China
fYear :
2015
Firstpage :
236
Lastpage :
240
Abstract :
The real-time compressive tracking algorithm, proposed by Kaihua Zhang etc. in 2012, is real-time and robust. But this algorithm may lead to object tracking losing in some complex environments, such as pose variation, illumination change, occlusion, and motion blur etc.. This paper improves the compressive tracking algorithm in two aspects: (1) we propose a self-adaptive method for learning parameter of the compressive tracking algorithm to enhance the robustness; (2)To solve the problem of losing tracking object, we propose a method using cosine algorithm to judge whether the object is lost and retrieve the lost object again. A number of video object tracking experiments show that the improved algorithm is more effective and efficient.
Keywords :
"Algorithm design and analysis","Real-time systems","Robustness","Classification algorithms","Target tracking","Feature extraction"
Publisher :
ieee
Conference_Titel :
Network and Information Systems for Computers (ICNISC), 2015 International Conference on
Type :
conf
DOI :
10.1109/ICNISC.2015.152
Filename :
7311876
Link To Document :
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