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An efficient human detection method for multi-pedestrian tracking

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Abstract

Traditional human detection using pre-trained detectors tends to be computationally intensive for time-critical tracking tasks, and the detection rate is prone to be unsatisfying when occlusion, motion blur and body deformation occur frequently. A spatial-confidential proposal filtering method (SCPF) is proposed for efficient and accurate human detection. It consists of two filtering phases: spatial proposal filtering and confidential proposal filtering. A compact spatial proposal is generated in the first phase to minimize the search space to reduce the computation cost. The human detector only estimates the confidence scores of the candidate search regions accepted by the spatial proposal instead of global scanning. At the second phase, each candidate search region is assigned with a supplementary confidence score according to their reliability estimated by the confidential proposal to reduce missing detections. The performance of the SCPF method is verified by extensive tests on several video sequences from available public datasets. Both quantitatively and qualitatively experimental results indicate that the proposed method can highly improve the efficiency and the accuracy of human detection.

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Authors and Affiliations

  1. Beijing Key Laboratory of Intelligent Information Technology (School of Computer Science, Beijing Institute of Technology), Beijing, 100081, China

    Wei-cun Xu  (许伟村) & Qing-jie Zhao  (赵清杰)

  2. School of Computer Science & Electronic Engineering, University of Essex, Colchester, CO4 3SQ, UK

    Huo-sheng Hu  (胡豁生)

Authors
  1. Wei-cun Xu  (许伟村)
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  2. Qing-jie Zhao  (赵清杰)
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  3. Huo-sheng Hu  (胡豁生)
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Corresponding author

Correspondence to Wei-cun Xu  (许伟村).

Additional information

Foundation item: Projects(61175096, 60772063) supported by the National Natural Science Foundation of China

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Xu, Wc., Zhao, Qj. & Hu, Hs. An efficient human detection method for multi-pedestrian tracking. J. Cent. South Univ. 20, 3552–3563 (2013). https://doi.org/10.1007/s11771-013-1881-4

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  • DOI: https://doi.org/10.1007/s11771-013-1881-4

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