Intelligent human detection method based on mixed RGB and infrared images

Yangyang Sun; Rufei Zhang; Ce Yang

doi:10.1117/12.2624910

13 December 2021 Intelligent human detection method based on mixed RGB and infrared images

Yangyang Sun, Rufei Zhang, Ce Yang

Proceedings Volume 12087, International Conference on Electronic Information Engineering and Computer Technology (EIECT 2021); 1208714 (2021) https://doi.org/10.1117/12.2624910
Event: International Conference on Electronic Information Engineering and Computer Technology (EIECT 2021), 2021, Kunming, China

Abstract

The rapid development of artificial intelligence technology has brought new research concepts and methods to military application. Aiming to accelerate the research process of intelligent sensing technology and promote the landing application of human detection technology, this paper studies maritime military targets detection methods in infrared image sources and establishes a special detection model for this task, which utilizes sufficient visible samples to realize the hetero-source detection of infrared imaging targets. A detection model for cross-domain targets is trained through sufficient visible images, which realizes accurate target recognition in infrared images. Target information of different domain images is then fused and optimized, advantages of different-domain images are considered, and target detection features and results are combined to boost the performance of military target detection, thus laying the foundation for maritime real-time reconnaissance applications. A human detection method based on bounding boxes and a human detection method based on key points in visible images are proposed, which improves the detection accuracy of occluded and small targets in UAV aerial images. In order to bridge the gap between infrared images and visible images and improve detection accuracy in infrared images, hetero-source detection methods based on feature alignment and shared feature are put forward. Experiments are carried out on test set which is composed of randomly selected 487 images, and the proposed model achieves 84.8 AP, which is 4.8 higher than the famous Faster R-CNN, which proves the effectiveness of the proposed method.

Citation Download Citation

Yangyang Sun, Rufei Zhang, and Ce Yang "Intelligent human detection method based on mixed RGB and infrared images", Proc. SPIE 12087, International Conference on Electronic Information Engineering and Computer Technology (EIECT 2021), 1208714 (13 December 2021); https://doi.org/10.1117/12.2624910

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KEYWORDS

Target detection

Infrared radiation

Infrared imaging

Visible radiation

Infrared detectors

Detection and tracking algorithms

Data modeling

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