Infrared image pedestrian detection based on deep convolutional neural network

Jiajia Gong; Yujuan Wang; Lixun Xie; Zikang Ma; Wei Shan

doi:10.1117/12.2655937

12 January 2023 Infrared image pedestrian detection based on deep convolutional neural network

Jiajia Gong, Yujuan Wang, Lixun Xie, Zikang Ma, Wei Shan

Proceedings Volume 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022); 1250921 (2023) https://doi.org/10.1117/12.2655937
Event: Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 2022, Guangzhou, China

Abstract

Pedestrian detection in infrared images has been a hot and difficult research topic in computer version. Traditional methods of pedestrian detection mainly depend on the manual feature for the expression of human body and the results largely relies on the feature representation. Designing artificial features is time-consuming and labor intensive, requires heuristic expertise and experience. Deep learning model based on convolution neural network can automatically learn feature representation from the original images, while avoiding the drawbacks of artificial features. Its difficulty is the choice of network parameters. In this paper, we propose to use deep learning method based on convolution neural network in the process of pedestrian detection. In addition, we analyze the impact of network layers, convolution kernel sizes and feature maps to pedestrian detection in infrared images. The results demonstrate the superiority of our method over traditional methods in detection rate and alarm rate.

Citation Download Citation

Jiajia Gong, Yujuan Wang, Lixun Xie, Zikang Ma, and Wei Shan "Infrared image pedestrian detection based on deep convolutional neural network", Proc. SPIE 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 1250921 (12 January 2023); https://doi.org/10.1117/12.2655937

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