Low, slow, small target recognition based on spatial vision network

Zhao Cheng; Pei Guo; Xin Qi

doi:10.1117/12.2287145

8 March 2018 Low, slow, small target recognition based on spatial vision network

Zhao Cheng; Pei Guo; Xin Qi

Author Affiliations +

Proceedings Volume 10609, MIPPR 2017: Pattern Recognition and Computer Vision; 106091I (2018) https://doi.org/10.1117/12.2287145
Event: Tenth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2017), 2017, Xiangyang, China

Abstract

Traditional photoelectric monitoring is monitored using a large number of identical cameras. In order to ensure the full coverage of the monitoring area, this monitoring method uses more cameras, which leads to more monitoring and repetition areas, and higher costs, resulting in more waste. In order to reduce the monitoring cost and solve the difficult problem of finding, identifying and tracking a low altitude, slow speed and small target, this paper presents spatial vision network for low-slow-small targets recognition. Based on camera imaging principle and monitoring model, spatial vision network is modeled and optimized. Simulation experiment results demonstrate that the proposed method has good performance.

Citation Download Citation

Zhao Cheng, Zhao Cheng, Pei Guo, Pei Guo, Xin Qi, Xin Qi, } "Low, slow, small target recognition based on spatial vision network", Proc. SPIE 10609, MIPPR 2017: Pattern Recognition and Computer Vision, 106091I (8 March 2018); doi: 10.1117/12.2287145; https://doi.org/10.1117/12.2287145

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