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High-density pedestrian detection algorithm based on deep information fusion

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Abstract

In order to improve the accuracy of high-density population detection, a high density pedestrian detection algorithm (YOLOv4-HDPD) is proposed based on deep information fusion. By increasing the connection points of cross-layer fusion, high-level semantic information is further integrated with feature information. The improved Iterative Self-Organizing Data Analysis algorithm (ISODATA) makes the anchor value more suitable for the network model without increasing the number of parameters. Moreover, the network anti-interference ability is increased by replacing the CIOU algorithm target detection object. Compared with the original network, the YOLOv4-HDPD network has improved in mAP and avgIOU. Under the premise that the detection speed of the network is basically not affected, mAP is increased by 5.28% and avgIOU is increased by 5.73%. In terms of the current results, the network algorithm has been improved the detection effect of high-density pedestrians. At the same time, the network provides a new idea for solving the clustering and detection of dense targets in real scenes.

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Acknowledgments

The authors would like to thank the editor and anonymous reviewers for their helpful comments and suggestions to improve the quality of this paper. This work was supported by National Natural Science Foundation of China (No.62003296), the Natural Science Foundation of Hebei (No.F2020203031), the College Students’ Innovative Entrepreneurial Training Plan Program (No.202010216014), Science and Technology Project of Hebei Education Department (No.QN2020225). Finally, the authors would like to thank EfficientDet [33], ATSS [34], and CenterMask [35] for their inspiration.

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Authors and Affiliations

  1. Yanshan University, Qinhuangdao, 066004, China

    Hexiang Zhang, Xiaofang Yang, Ziyu Hu, Ruoxin Hao, Zehang Gao & Jianhao Wang

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  1. Hexiang Zhang
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  2. Xiaofang Yang
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  3. Ziyu Hu
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Correspondence to Xiaofang Yang.

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Zhang, H., Yang, X., Hu, Z. et al. High-density pedestrian detection algorithm based on deep information fusion. Appl Intell 52, 15483–15495 (2022). https://doi.org/10.1007/s10489-022-03354-1

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