Research on detection and tracking technology of optoelectronic system based on deep neural network

Zuofeng Zhou; Hao Liu; Junhong Yang

doi:10.1117/12.2659629

23 November 2022 Research on detection and tracking technology of optoelectronic system based on deep neural network

Zuofeng Zhou, Hao Liu, Junhong Yang

Proceedings Volume 12454, International Symposium on Robotics, Artificial Intelligence, and Information Engineering (RAIIE 2022); 1245407 (2022) https://doi.org/10.1117/12.2659629
Event: International Symposium on Robotics, Artificial Intelligence, and Information Engineering (RAIIE 2022), 2022, Hohhot, China

Abstract

Photoelectric tracking systems are widely used in the fields of reconnaissance, communication, and measurement. Due to different application scenarios, photoelectric tracking systems often face various interference problems such as complex backgrounds, similar targets, blurred camera motion, poor lighting, and strong mobility of moving targets, which have become a huge challenge for photoelectric detection systems. In order to improve the performance of the optoelectronic tracking system as a whole, this paper studies the monitoring and tracking technology of the optoelectronic system based on the deep neural network. This paper proposes a diagonal network and peak response regularization technology for the task of photoelectric detection target detection. The diagonal network can effectively detect the data, and the peak response regularization method regularizes the eigenvalues in the deep neural network. Plug and play is combined with common target detection tasks, which can effectively improve the effect of target detection and tracking without increasing the amount of calculation. The validation results on public datasets and UAV datasets show that the related technologies have achieved good results in photoelectric detection and tracking tasks such as human pose detection and image classification.

Citation Download Citation

Zuofeng Zhou, Hao Liu, and Junhong Yang "Research on detection and tracking technology of optoelectronic system based on deep neural network", Proc. SPIE 12454, International Symposium on Robotics, Artificial Intelligence, and Information Engineering (RAIIE 2022), 1245407 (23 November 2022); https://doi.org/10.1117/12.2659629

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KEYWORDS

Neural networks

Target detection

Detection and tracking algorithms

Optoelectronics

Head

Unmanned aerial vehicles

Convolutional neural networks

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