Barefoot pressure image recognition and analysis in natural walking state based on selective fusion attention network

Wenxia Bao; Qiuju Xu; Nian Wang; Xianjun Yang

doi:10.1117/12.2652401

10 November 2022 Barefoot pressure image recognition and analysis in natural walking state based on selective fusion attention network

Wenxia Bao, Qiuju Xu, Nian Wang, Xianjun Yang

Author Affiliations +

Proceedings Volume 12331, International Conference on Mechanisms and Robotics (ICMAR 2022); 1233148 (2022) https://doi.org/10.1117/12.2652401
Event: International Conference on Mechanisms and Robotics (ICMAR 2022), 2022, Zhuhai, China

Abstract

Footprint is a human biological trait with a high extraction rate from crime scenes. It plays an essential role in criminal investigation and security operations. The majority of footprint studies are currently conducted under controlled conditions. However, footprints formed under natural walking are affected by physiological and behavioral characteristics such as posture and walking state, and have variability, which makes it difficult to accurately identify footprints. In this paper, multi-state barefoot pressure images under natural walking state are taken as the research object, and the selective attention network is used for high precision recognition. It can provide a theoretical foundation as well as technical support for later comparison and identification of footprints on-site.

Citation Download Citation

Wenxia Bao, Qiuju Xu, Nian Wang, and Xianjun Yang "Barefoot pressure image recognition and analysis in natural walking state based on selective fusion attention network", Proc. SPIE 12331, International Conference on Mechanisms and Robotics (ICMAR 2022), 1233148 (10 November 2022); https://doi.org/10.1117/12.2652401

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