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Video tracking technology based on improved compressed sensing algorithm
Author(s): Zhemin Zhuang; Naihai Lei; Alex Noel Josephraj
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Paper Abstract

The video tracking technology is applied widely in military field, intelligent monitoring, security and human-computer interaction fields. In the paper, the neighborhood and dimension of the descriptor of SIFT (Scale Invariant Feature Transform, SIFT) is discussed, then a novel updating strategy of the learning rate of the classifier in the compressive theory is proposed. Target drifting phenomena and occlusion are handled properly after combined with efficient SIFT feature descriptor and improved compressed sensing algorithm. The experiments show that this method not only can improve the real-time performance of tracking target, but also can carry on the tracking of moving target accurately in the event of a target drifting and occlusion.

Paper Details

Date Published: 9 August 2018
PDF: 5 pages
Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 1080641 (9 August 2018); doi: 10.1117/12.2502822
Show Author Affiliations
Zhemin Zhuang, Shantou Univ. (China)
Naihai Lei, Shantou Univ. (China)
Alex Noel Josephraj, Shantou Univ. (China)


Published in SPIE Proceedings Vol. 10806:
Tenth International Conference on Digital Image Processing (ICDIP 2018)
Xudong Jiang; Jenq-Neng Hwang, Editor(s)

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