Pedestrian Occlusion Tracking Algorithm Based on Improved DSST
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    Abstract:

    In order to solve the problem that the discriminative scale space tracking (DSST) algorithm cannot track when pedestrians reappear after being completely occluded for a long time, an improved tracking algorithm (DDSST) is proposed. Under the DSST framework, pedestrian tracking is first performed. And then the high confidence index calculation strategy is introduced as the tracking accuracy credibility feedback mechanism. when the tracking is lost, the deformable part model (DPM) is used to relocate the tracking target. Finally, the accuracy of the DDSST algorithm is verified by evaluating the online Object target Tracking Benchmark (OTB) dataset and the video sequences captured in the actual environment, and compared with other tracking algorithms. Experimental analysis shows that the distance precision and success rate of the improved algorithm are improved by 4.1% and 6% compared with DSST, and the performance is better than other algorithms, and the tracking performed under conditions such as deformation, occlusion, out-of-plane rotation, motion blur, and scale transformation is more stable.

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赵梦萍,熊凌,陈洋.基于改进DSST的行人遮挡跟踪算法.计算机系统应用,2020,29(11):168-175

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History
  • Received:March 24,2020
  • Revised:April 21,2020
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  • Online: October 30,2020
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