A Method of Hand Contour Tracking based on GVF, Corner and Optical flow

DOI

10.2991/mmeceb-15.2016.107How to use a DOI?

Keywords

GVF Snake, SUSAN Corner, Optical flow

Abstract

Since bare human hand is highly articulated and deformable, its tracking is more challenging than rigid object tracking. In this paper, an automatic approach is proposed to track hand contour on the basis of gradient vector flow (GVF Snake), corner detection and sparse optical flow. The skin-color model and motion information help to reduce the impact of local minimal under complex background. To lower the sensitivity of GVF Snake to initial contour, a curvature-difference-based corner detection is proposed to effectively detect enough corners on hand contour and sparse optical flow is applied to ensure a robust tracking of these corners even with violent gesture change. The experiments have shown a promising hand contour tracking using real image sequence under the usual lighting condition in lab.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ke Du
AU  - Ying Shi
AU  - Jie Chen
AU  - MingJun Sun
AU  - ShuHai Quan
PY  - 2015/12
DA  - 2015/12
TI  - A Method of Hand Contour Tracking based on GVF, Corner and Optical flow
BT  - Proceedings of the 2015 2nd International Conference on Machinery, Materials Engineering, Chemical Engineering and Biotechnology
PB  - Atlantis Press
SP  - 542
EP  - 549
SN  - 2352-5401
UR  - https://doi.org/10.2991/mmeceb-15.2016.107
DO  - 10.2991/mmeceb-15.2016.107
ID  - Du2015/12
ER  -