Computer and Modernization

Previous Articles     Next Articles

 An Improved TLD Visual Target Tracking Method

  

  1. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
  • Received:2015-01-05 Online:2015-04-27 Published:2015-04-29

Abstract:

Tracking-Learning-Detection (TLD) is a new tracking algorithm proposed by Zdenek Kalal. The most obvious difference between TLD and the traditional tracking
algorithm is that TLD combines traditional tracking algorithm with traditional detection algorithm to solve problems such as deformation and partial occlusion which may happen
when target is followed during the tracking procedure. The TLD is improved by this paper, based on Meanshift and Kalman, this paper introduces prediction for the area where
current frame target is located into testing module of the algorithm, which is supposed to narrow detection range of detector effectively and reduce the computation burden of
the algorithm; variance classifier in original algorithm is replaced by color feature classifier, which improve performance of target recognition. what’s more, the improvement
of integrated modular can increase the rate of success for target tracking. After comparison of the improved TLD and original TLD, the result shows that the improved TLD
algorithm has high accuracy and better precision for tracking.

Key words:  TLD, target tracking, target area prediction, color feature