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Feature-Scoring-Based Multi-cue Infrared Object Tracking

  • Jiangtao Wang
  • Debao Chen
  • Suwen Li
  • Yijun Yang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7751)

Abstract

In this paper, we propose an effective tracker for infrared videos based on the multi-cue fusion. Under the particle filter tracking construction, a novel feature scoring scheme is introduced to evaluate different cue tracking ability, then the multi-cue fusion is executed in a weighted sum manner. In our tracking system, the score of each feature can be adaptively updated according to the current environment. Experimental results with various Infrared Video Database and different trackers are reported to demonstrate the accuracy and robustness of our algorithm.

Keywords

infrared video object tracking multi-cue fusion particle filter 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Jiangtao Wang
    • 1
  • Debao Chen
    • 1
  • Suwen Li
    • 1
  • Yijun Yang
    • 1
  1. 1.Huaibei Normal UniversityHuaibeiChina

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