Robust human joint positioning with a single-pixel detector

Guojing Geng; Aleksander Tsoy; Zihan Geng; Yongbin Zhou

doi:10.1117/12.3048574

5 December 2024 Robust human joint positioning with a single-pixel detector

Guojing Geng, Aleksander Tsoy, Zihan Geng, Yongbin Zhou

Author Affiliations +

Proceedings Volume 13418, Fifteenth International Conference on Information Optics and Photonics (CIOP 2024); 134182N (2024) https://doi.org/10.1117/12.3048574
Event: 15th International Conference on Information Optics and Photonics (CIOP2024), 2024, Xi’an, China

Abstract

The progress of imaging technologies has raised significant concerns regarding privacy and data transmission. Traditional imaging systems capture high-resolution images containing more personal information than necessary, posing privacy risks and requiring substantial computational resources. To address this issue, we propose a semi-image-free single-pixel imaging framework for human detection and pose estimation. The proposed model reconstructs only essential image regions, specifically bounding boxes containing humans, utilizing one-dimensional signals, thereby enhancing privacy and reducing data processing requirements. Simulations on the Microsoft COCO dataset are performed, showing our method is robust to the background noise. Our method operates efficiently with a low sampling ratio of approximately 3.5%, highlighting its suitability for resource-constrained environments.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Guojing Geng, Aleksander Tsoy, Zihan Geng, and Yongbin Zhou "Robust human joint positioning with a single-pixel detector", Proc. SPIE 13418, Fifteenth International Conference on Information Optics and Photonics (CIOP 2024), 134182N (5 December 2024); https://doi.org/10.1117/12.3048574

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