• Infrared Technology
  • Vol. 44, Issue 12, 1316 (2022)
Jie KANG1, Ye TIAN1, and Gang YANG2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: Cite this Article
    KANG Jie, TIAN Ye, YANG Gang. Research on Crowd Abnormal Behavior Detection Based on Improved SSD[J]. Infrared Technology, 2022, 44(12): 1316 Copy Citation Text show less

    Abstract

    Aiming at the problems of high algorithmic complexity and low detection accuracy caused by overlapping occlusions in abnormal crowd behavior detection, this paper proposes an algorithm for crowd abnormal behavior detection based on an improved single-shot multi-box detector(SSD). First, the lightweight network MobileNet v2 was used to replace the original feature extraction network VGG-16, and a convolutional layer was constructed by a deformable convolution module to enhance the receptive field. Feature enhancement was performed by integrating the position information into the channel attention, which can capture long-range dependencies between spatial locations, allowing for better handling of overlapping occlusions. The experimental results show that the proposed algorithm has a good detection effect on abnormal crowd behavior.
    KANG Jie, TIAN Ye, YANG Gang. Research on Crowd Abnormal Behavior Detection Based on Improved SSD[J]. Infrared Technology, 2022, 44(12): 1316
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