Adaptive and discriminative metric differential tracking

Nan Jiang*, Wenyu Liu, Ying Wu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

36 Scopus citations

Abstract

Matching the visual appearances of the target over consecutive image frames is the most critical issue in video-based object tracking. Choosing an appropriate distance metric for matching determines its accuracy and robustness, and significantly influences the tracking performance. This paper presents a new tracking approach that incorporates adaptive metric into differential tracking method. This new approach automatically learns an optimal distance metric for more accurate matching, and obtains a closed-form analytical solution to motion estimation and differential tracking. Extensive experiments validate the effectiveness of adaptive metric, and demonstrate the improved performance of the proposed new tracking method.

Original languageEnglish (US)
Title of host publication2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011
Pages1161-1168
Number of pages8
DOIs
StatePublished - Sep 22 2011
Event2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011 - Colorado Springs, CO, United States
Duration: Jun 20 2011Jun 25 2011

Other

Other2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011
CountryUnited States
CityColorado Springs, CO
Period6/20/116/25/11

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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    Jiang, N., Liu, W., & Wu, Y. (2011). Adaptive and discriminative metric differential tracking. In 2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011 (pp. 1161-1168). [5995716] https://doi.org/10.1109/CVPR.2011.5995716