吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (增刊1): 239-243.

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Parallelized annealed particle filter

BIAN Ya-tao, ZHAO Xu, SONG Jian, LIU Yun-cai   

  1. School of Electronic Information and Electrical Engineering, Shanghai Jiaotong University, Shanghai 200240, China
  • Received:2012-05-20 Published:2013-06-01

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Abstract:

A parallelized Annealed Particle Filter method via heterogeneous computing (P-APF) was proposed,to implement real-time marker-less motion tracking based on OpenCL framework.The overall computing procedure in P-APF was decomposed into several computational tasks with corresponding granularity.According to the degree of parallelism,the tasks were assigned to standard and attached processors respectively,to fully leverage heterogeneous computing ability.A novel task latency hidden strategy was proposed to further reduce time cost.Experiments on different human motion datasets demonstrate that P-APF can achieve real-time tracking performance without losing accuracy.With an average acceleration ratio of 106 compared to serial implementation,the time cost basically remains constant with the growth of particle number and view number in a limited range.

Key words: parallelization, annealed particle filter, marker-less motion tracking, heterogeneous computing, OpenCL

CLC Number: 

  • TG156

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