Abstract

The kernel based tracking has two disadvantages: the tracking window size cannot be adjusted efficiently, and the kernel based color distribution may not have enough ability to discriminate object from clutter background. For boosting up the feature's discriminating ability, both scale invariant features and kernel based color distribution features are used as descriptors of tracked object. The proposed algorithm can keep tracking object of varying scales even when the surrounding background is similar to the object's appearance.

© 2008 Chinese Optics Letters

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  1. A. Li, Z. Jing, and S. Hu, Chin. Opt. Lett. 3, 326 (2005).
  2. D. Comaniciu, V. Ramesh, and P. Meer, IEEE Trans. Pattern Anal. Mach. Intell. 25, 564 (2003).
  3. D. G. Lowe, Int. J. Computer Vision 60, 91 (2004).
  4. N. Peng, J. Yang, and Z. Liu, Opt. Eng. 44, 7 (2005).
  5. R. Collins, in Proceedings of 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition II-234 (2003).
  6. M. Isard and A. Blake, Int. J. Computer Vision 29, 5 (1998).

2005

N. Peng, J. Yang, and Z. Liu, Opt. Eng. 44, 7 (2005).

A. Li, Z. Jing, and S. Hu, Chin. Opt. Lett. 3, 326 (2005).

2004

D. G. Lowe, Int. J. Computer Vision 60, 91 (2004).

2003

D. Comaniciu, V. Ramesh, and P. Meer, IEEE Trans. Pattern Anal. Mach. Intell. 25, 564 (2003).

1998

M. Isard and A. Blake, Int. J. Computer Vision 29, 5 (1998).

Chin. Opt. Lett.

IEEE Trans. Pattern Anal. Mach. Intell.

D. Comaniciu, V. Ramesh, and P. Meer, IEEE Trans. Pattern Anal. Mach. Intell. 25, 564 (2003).

Int. J. Computer Vision

D. G. Lowe, Int. J. Computer Vision 60, 91 (2004).

M. Isard and A. Blake, Int. J. Computer Vision 29, 5 (1998).

Opt. Eng.

N. Peng, J. Yang, and Z. Liu, Opt. Eng. 44, 7 (2005).

Other

R. Collins, in Proceedings of 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition II-234 (2003).

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