City Research Online

Abstract

Realistic 3D modeling of human hand anatomy has a number of important applications, including real-time tracking, pose estimation, and human-computer interaction. However the use of RGB-D sensors to accurately capture the full 3D shape of a hand is limited by self-occlusions, relatively smaller size of the hand and the requirement to capture multiple images. In this paper, we propose a method for generating a detailed, realistic hand model from a single frontal range scan and registered color image. In essence, our method converts this 2.5D data into a fully 3D model. The proposed approach extracts joint locations from the color image using a fingertip and interfinger region detector with a Naive Bayes probabilistic model. Direct correspondence between these joint locations in the range scan and a synthetic hand model are used to perform rigid registration, followed by a thin-plate-spline deformation that non-rigidly registers a synthetic model. This reconstructed model maintains similar geometric properties as the range scan, but also includes the back side of the hand. Experimental results demonstrate the promise of the method to produce detailed and realistic 3D hand geometry.

Publication Type:	Conference or Workshop Item (Paper)
Additional Information:	© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Publisher Keywords:	Hand model, pose estimation, reconstruction
Subjects:	R Medicine > RC Internal medicine T Technology > TA Engineering (General). Civil engineering (General)
Departments:	School of Science & Technology > Computer Science

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