New Techniques for Hand Pose Estimation Based on Kinect Depth Data
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Date
2014
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
In this paper we present new techniques for extension and improvement of approaches to markerless 3D hand pose estimation: A new algorithm for finger segmentation in point clouds of hands is presented which makes use of the narrow and flexible shape of the fingers. The kinematic of a 3D hand model gets aligned to the geodesic paths of the fingers which provides a very natural configuration of the model. Therefore a new technique for optimization of those geodesic paths is introduced. Another benefit of this system is, that it's only data resource is the depth stream of a Kinect. So no additional hardware, markers or training data is needed. A first implementation of our approach provides a proof for the new concepts and looks promising for further investigation.
Description
@inproceedings{:10.2312/eurovr.20141355,
booktitle = {EuroVR 2014 - Conference and Exhibition of the European Association of Virtual and Augmented Reality},
editor = {Jerome Perret and Valter Basso and Francesco Ferrise and Kaj Helin and Vincent Lepetit and James Ritchie and Christoph Runde and Mascha van der Voort and Gabriel Zachmann},
title = {{New Techniques for Hand Pose Estimation Based on Kinect Depth Data}},
author = {Hummel, Simon and Haefner, Victor and Haefner, Polina and Ovtcharova, Jivka},
year = {2014},
publisher = {The Eurographics Association},
ISBN = {978-3-905674-76-7},
DOI = {/10.2312/eurovr.20141355}
}