Paper
23 May 2023 Video detection method of pointer instrument based on improved FCOS
Author Affiliations +
Proceedings Volume 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022); 1260403 (2023) https://doi.org/10.1117/12.2674694
Event: 2nd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 2022, Guangzhou, China
Abstract
Aiming at the problem that pointer instrument detection algorithm has slow locating speed and low real time performance in edge equipment, this paper proposes a pointer instrument video detection method based on improved FCOS. The algorithm is based on FCOS model and uses lightweight network ShuffleNetV2 to extract image features. Using PAN structure to strengthen the original feature fusion network, a bidirectional feature fusion network is formed. The attention module with global context information is introduced to reduce the information attenuation in the process of feature fusion. The two parameters of pixel utilization PUR and relative time increase RIT are introduced to test the influence of images with different image pixels on the detection effect in a more intuitive form. Through experiments, when the resolution of the input image pixel is 1280×1280, compared with the baseline model, the detection time of the pointer instrument video detection method based on improved FCOS is reduced by 91.60% when the detection accuracy is similar.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xi Chen, Pengfei Zhang, Wei Xu, Yongjuan Chang, Mingshuo Liu, and Zhenyuan Zhao "Video detection method of pointer instrument based on improved FCOS", Proc. SPIE 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 1260403 (23 May 2023); https://doi.org/10.1117/12.2674694
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KEYWORDS
Equipment

Feature fusion

Video

Object detection

Target detection

Feature extraction

Image resolution

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