A Review on Vision-Based Full DOF Hand Motion Estimation

Authors:
Ali Erol;George Bebis;Mircea Nicolescu;Richard D. Boyle;Xander Twombly
Affiliations:
University of Nevada, Reno;University of Nevada, Reno;University of Nevada, Reno;BioVis Laboratory, NASA Ames Research Center,;BioVis Laboratory, NASA Ames Research Center,
Venue:
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Year:
2005

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Abstract

Direct use of the hand as an input device is an attractive method for providing natural human-computer interaction (HCI). Currently, the only technology that satisfies the advanced requirements of hand-based input for HCI is glovebased sensing. This technology, however, has several drawbacks including that it hinders the ease and naturalness with which the user can interact with the computer controlled environment, and it requires long calibration and setup procedures. Computer vision has the potential to provide much more natural, non-contact solutions. As a result, there have been considerable research efforts to use the hand as an input device for HCI. A very challenging problem in this context, which is the focus of this review, is recovering the 3D pose of the hand and the fingers as glove-based devices do. This paper presents a brief literature review on full degreeof- freedom (DOF) hand motion estimation methods.