Tracking low resolution objects by metric preservation

Nan Jiang*, Wenyu Liu, Heng Su, Ying Wu

*Corresponding author for this work

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

14 Scopus citations

Abstract

Tracking low resolution (LR) targets is a practical yet quite challenging problem in real applications. The loss of discriminative details in the visual appearance of the L-R targets confronts most existing visual tracking methods. Although the resolution of the LR video inputs may be enhanced by super resolution (SR) techniques, the large computational cost for high-quality SR does not make it an attractive option. This paper presents a novel solution to track LR targets without performing explicit SR. This new approach is based on discriminative metric preservation that preserves the structure in the high resolution feature space for LR matching. In addition, we integrate metric preservation with differential tracking to derive a closed-form solution to motion estimation for LR video. Extensive experiments have demonstrated the effectiveness and efficiency of the proposed approach.

Original languageEnglish (US)
Title of host publication2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011
Pages1329-1336
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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