Computer Science ›› 2017, Vol. 44 ›› Issue (3): 307-312.doi: 10.11896/j.issn.1002-137X.2017.03.062

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Inter-frame Consistency Structured Sparse Representation Object Tracking Algorithm

HOU Yue-en and LI Wei-guang   

  • Online:2018-11-13 Published:2018-11-13

Abstract: Object tracking technology is widely used in daily life and production.Howe 〖BHDWG1,WK42,WK43,WK42W〗第3期 侯跃恩,等:帧间连续结构稀疏表示的目标跟踪算法 ver,designing a accurate,robust and real-time object tracker is still a challenging task.For improving the performance of tracking algorithm,an inter-frame consistency structured sparse representation object tracking algorithm was designed.The algorithm is carried out under the framework of particle filter,and uses the principle of structured sparse representation to recombine candidate targets.Firstly,the dictionary is constructed by target and background templates.Hence the ability of discriminating target and background is improved.Secondly,a structured sparse representation objective function,which contains inter-frame consistency constraint term,is built.The function is able to decide targets by using the consistency of target state.Thirdly,according to the residual error information,a likelihood measurement is developed.Comparing to traditional likelihood measurements,the proposed measurement is insensitive to similar target.Finally,the proposed tracking algorithm was proved to be more robust and accurate through 6 compared experiments.

Key words: Object tracking,Sparse coefficient,Particle filter,Sparse representation,Inter-frame consistency

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