A Point-to-Point Tracking Algorithm Based on the Theory of Floating Pixels

WANG Shoujue; JIANG Yuwen; TAN Leyi

doi:10.1049/cje.2016.01.001

Volume 25 Issue 1

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WANG Shoujue, JIANG Yuwen, TAN Leyi, “A Point-to-Point Tracking Algorithm Based on the Theory of Floating Pixels,” Chinese Journal of Electronics, vol. 25, no. 1, pp. 1-5, 2016, doi: 10.1049/cje.2016.01.001

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WANG Shoujue, JIANG Yuwen, TAN Leyi, “A Point-to-Point Tracking Algorithm Based on the Theory of Floating Pixels,” Chinese Journal of Electronics, vol. 25, no. 1, pp. 1-5, 2016, doi: 10.1049/cje.2016.01.001

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A Point-to-Point Tracking Algorithm Based on the Theory of Floating Pixels

doi: 10.1049/cje.2016.01.001

WANG Shoujue^1,2,
JIANG Yuwen^{1,2
,},
TAN Leyi^2,3

1.
Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, China;
2.
Suzhou Institute of Nano-Tech and Nano-Biotics, Chinese Academy of Sciences, Suzhou 215123, China;
3.
College of Electronics and Information Engineering, Tongji University, Shanghai 200092, China

Funds: This work is supported by the National Natural Science Foundation of China (No.90920013).

More Information

Corresponding author: JIANG Yuwen (corresponding author) was born in 1986. She received the B.S. degree from School of Electronics Engineering and Computer Science, Peking University, in 2008. She is now a Ph.D. candidate in the Institute of Semiconductor, Chinese Academy of Sciences since 2008. Her research interests include Biomimetic pattern recognition, computer vision and image processing. (Email: ywjiang2009@sinano.ac.cn)
Received Date: 2014-04-08
Rev Recd Date: 2014-06-11
Publish Date: 2016-01-10

Abstract

Abstract

Based on the theory of floating pixels, a point-to-point tracking algorithm based on local features is presented. A novel texture-based feature set is proposed in a form of high dimensional vector which describes each single point. Point-to-point matching is applied in a way of vector operation at multiple scales. Each match is verified by variance analysis, and unreliable matches are corrected with candidates available. Experimental results demonstrate that this algorithm maintains strong robustness when target-appearance is varying and environment is complex.
- Floating pixels,
- Displacement vector field (DVF),
- Object tracking,
- Texture descriptor,
- High dimensional biomimetic informatics,
- Points matching

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References(13)

References

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