Real-time tracking of articulated human models using a 3D shape-from-silhouette method

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Abstract

This paper describes a system, which acquires 3D data and tracks an eleven degree of freedom human model in real-time. Using four cameras we create a time-varying volumetric image (a visual hull) of anything moving in the space observed by all four cameras. The sensor is currently operating in a volume of approximately 500,000 voxels (1.5 inch cubes) at a rate of 25 Hz. The system is able to track the upper body dynamics of a human (x,y position of the body, a torso rotation, and four rotations per arm). Both data acquisition and tracking occur on one computer at a rate of 16 Hz. We also developed a calibration procedure, which allows the system to be moved and be recalibrated quickly. Furthermore we display in real-time, either the data overlaid with the joint locations or a human avatar. Lastly our system has been implemented to perform crane gesture recognition.

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Luck, J., Small, D., & Little, C. Q. (2001). Real-time tracking of articulated human models using a 3D shape-from-silhouette method. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1998, pp. 19–26). Springer Verlag. https://doi.org/10.1007/3-540-44690-7_3

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