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Multitarget Pedestrian Tracking Algorithm Based on a Contour Template with Multiscale Stability

Author

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  • Hui Liu
  • Yingying Feng
  • Shigan Yu
  • Wen-Tsao Pan

Abstract

In order to overcome the problems of high error rate and poor tracking effect of traditional tracking algorithms, a multitarget pedestrian tracking algorithm based on a contour template is designed in this paper. The pedestrian template is divided into several contour regions by template voting strategy and pedestrian features are classified by regional feature similarity classification. Then, the score function is selected to realize the multiobjective pedestrian feature division, and the multicontour template matching is realized according to the similarity of deformation diversity. According to the matching results, the detection and tracking of multitarget objects are realized. The experimental results show that the feature recognition accuracy of the algorithm is between 93% and 98%, the tracking error of pedestrian gravity center position is always below 5%, and the tracking time is always below 5 S in different video frame scales, which fully proves the effectiveness of the algorithm.

Suggested Citation

  • Hui Liu & Yingying Feng & Shigan Yu & Wen-Tsao Pan, 2022. "Multitarget Pedestrian Tracking Algorithm Based on a Contour Template with Multiscale Stability," Discrete Dynamics in Nature and Society, Hindawi, vol. 2022, pages 1-8, September.
    • Handle: RePEc:hin:jnddns:6872596
    DOI: 10.1155/2022/6872596
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