Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (5): 190-196.DOI: 10.3778/j.issn.1002-8331.2003-0070

Previous Articles     Next Articles

Research on Detection of People with Camouflage Pattern via Improving RetinaNet

DENG Xiaotong, CAO Tieyong, FANG Zheng, ZHENG Yunfei   

  1. 1.Institute of Command and Control Engineering, Army Engineering University, Nanjing 210000, China
    2.Chinese People’s Liberation Army Artillery Air Defense Academy, Nanjing 210000, China
  • Online:2021-03-01 Published:2021-03-02



  1. 1.陆军工程大学 指挥控制工程学院,南京 210000
    2.中国人民解放军炮兵防空兵学院南京校区,南京 210000


Camouflage technology can effectively reduce the visual significance of the objects, which conduce a huge challenge to camouflage objects detection. Based on RetinaNet detection framework, spatial attention and channel attention modules are embeded for camouflage features extraction, and a new prediction box filtering algorithm is built based on positioning confidence score, which effectively realizes the detection for camouflage personnel. Experimental results on the extended camouflage dataset show that the average detection accuracy of the proposed model reaches 93.1%, which improves by 8.7 percentage points.

Key words: object detection, camouflage, attention mechanism



关键词: 目标检测, 迷彩伪装, 注意力机制