Using autofocus data for 3D hand interaction

Chan-Yuan Huang; Chen-Han Lin; Homer H. Chen

doi:10.1117/12.3000801

12 March 2024 Using autofocus data for 3D hand interaction

Chan-Yuan Huang, Chen-Han Lin, Homer H. Chen

Author Affiliations +

Proceedings Volume 12913, Optical Architectures for Displays and Sensing in Augmented, Virtual, and Mixed Reality (AR, VR, MR) V; 129130L (2024) https://doi.org/10.1117/12.3000801
Event: SPIE AR | VR | MR, 2024, San Francisco, California, United States

Abstract

Hand tracking algorithms relying on a single camera as the sensing device can only provide relative depth information, resulting in limited practicality. This limitation underscores the necessity for effective and accurate estimation of the absolute distances between hand joints and the camera in the real world. We respond to this pressing need by introducing a methodology that exploits the autofocus functionality of a camera for hand tracking. It takes advantage of the unutilized potential of a camera and removes the need for additional power-demanding and costly depth sensors to accurately estimate the absolute distances of hand joints. Our methodology undergoes rigorous experimental validation and consistently outperforms traditional methods across different lens positions.

Conference Presentation

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

Citation Download Citation

Chan-Yuan Huang, Chen-Han Lin, and Homer H. Chen "Using autofocus data for 3D hand interaction", Proc. SPIE 12913, Optical Architectures for Displays and Sensing in Augmented, Virtual, and Mixed Reality (AR, VR, MR) V, 129130L (12 March 2024); https://doi.org/10.1117/12.3000801

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