A Tracking Algorithm Based on SIFT Feature and Particle Filter with Epipolar Constraint

Abstract

Abstract:

To deal with the instability in the target tracking method based on color or edge features, a tracking algorithm based on SIFT features
and particle filter with epipolar constraint was proposed in this paper. In this method, the target template was established using the vectors of the SIFT feature points, and the epiploar constraint was used to improve the target matching accuracy. A particle filter method was employed to establish the candidate template of SIFT feature vectors, and a likelihood function was used to calculate the similarity between the candidate template and the target template. Experimental results show that the proposed algorithm can track the target when the color of target is similar to one of the background, and it still works well when the posture or shape of the target changes.

Key words: target tracking, epipolar constraint, scaleinvariant feature transform (SIFT), particle filter

CLC Number:

TP 391

LIU Shirong1,2，WU Chu1,3,ZHANG Botao1,2,ZHANG Haibing1,2. A Tracking Algorithm Based on SIFT Feature and Particle Filter with Epipolar Constraint[J]. Journal of Shanghai Jiaotong University, 2014, 48(07): 1026-1032.

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