An Improved Algorithm on Adaptive KLT Vision Tracking

Abstract:

In view of the shortage of the KLT (Kanade-Lucas-Tomasi) tracking algorithm, an improved adaptive tracking method based on KLT is proposed in this paper, in which a kind of filtering mechanism is applied to decrease the effects of noise and illumination on tracking system. In order to eliminate the error of tracking, the strategies based on forward-backward error and measurement validity are utilized properly. However, because the approach to forward-backward error makes the feature points reduce, which leads to tracking failure especially when the shapes of object change, a method for appending the feature points is introduced. Experimental results indicate that the method presented in this paper is state of the art robustness in our comparison with related work and demonstrate improved generalization over the conventional methods.

• Periodical: Advanced Materials Research (Volumes 631-632)
• Pages: 1270-1275
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.631-632.1270
• Online since: January 2013
• Authors: Yuan Min Liu, Lian Fang Tian
• Keywords: Adaptive, Forward-Backward Error, KLT, Vision Tracking

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