Earticle

초록

영어

In this paper, we propose a fast and robust tracking method based on reversed sparse representation. Be different from other sparse representation based visual tracking methods, the target template is sparsely represented by the candidate particles which are gotten by particle filter. In order to improve the robustness of the method, we use a target template set. Meanwhile, a two level competition mechanism is also introduced. In the first level, each target template is sparsely represented and all the candidate particles compete with each other by a similarity calculation, which is based on sparse coefficients. Then, the winners construct a target candidate set. In the second level, all the target candidates in the target candidate set compete with each other and the one which is the most similar to the template set is considered as the target. In addition, a template set update strategy is proposed to adapt the appearance variations of the target. Experimental results on challenging benchmark video sequences demonstrate that the proposed tracking algorithm performs favorably against several state-of-the-art methods.

목차

Abstract
 1. Introduction
 2. Reversed Sparse Representation
 3. Visual Tracking Based on Reversed Sparse Representation
  3.1. First Level Competition
  3.2. Second Level Competition
  3.3. Template Update
  3.4. Summary of the Proposed Visual Tracking Algorithm
 4. Experimental Results
  4.1. Evaluation the Time Cost of the Trackers
  4.2. Evaluation the Accuracy of the Trackers
 5. Conclusion
 References

키워드

저자

• Wenhui Dong [ College of Physics and Electronic Engineering, Dezhou University, Dezhou 253023, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605