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Efficient visual object tracking with online nearest neighbor classifier

Publication ,  Journal Article
Gu, S; Zheng, Y; Tomasi, C
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
March 16, 2011

A tracking-by-detection framework is proposed that combines nearest-neighbor classification of bags of features, efficient subwindow search, and a novel feature selection and pruning method to achieve stability and plasticity in tracking targets of changing appearance. Experiments show that near-frame-rate performance is achieved (sans feature detection), and that the state of the art is improved in terms of handling occlusions, clutter, changes of scale, and of appearance. A theoretical analysis shows why nearest neighbor works better than more sophisticated classifiers in the context of tracking. © 2011 Springer-Verlag Berlin Heidelberg.

Duke Scholars

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

March 16, 2011

Volume

6492 LNCS

Issue

PART 1

Start / End Page

271 / 282

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

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Gu, S., Zheng, Y., & Tomasi, C. (2011). Efficient visual object tracking with online nearest neighbor classifier. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6492 LNCS(PART 1), 271–282. https://doi.org/10.1007/978-3-642-19315-6_21
Gu, S., Y. Zheng, and C. Tomasi. “Efficient visual object tracking with online nearest neighbor classifier.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6492 LNCS, no. PART 1 (March 16, 2011): 271–82. https://doi.org/10.1007/978-3-642-19315-6_21.
Gu S, Zheng Y, Tomasi C. Efficient visual object tracking with online nearest neighbor classifier. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2011 Mar 16;6492 LNCS(PART 1):271–82.
Gu, S., et al. “Efficient visual object tracking with online nearest neighbor classifier.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6492 LNCS, no. PART 1, Mar. 2011, pp. 271–82. Scopus, doi:10.1007/978-3-642-19315-6_21.
Gu S, Zheng Y, Tomasi C. Efficient visual object tracking with online nearest neighbor classifier. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2011 Mar 16;6492 LNCS(PART 1):271–282.

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

March 16, 2011

Volume

6492 LNCS

Issue

PART 1

Start / End Page

271 / 282

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences