Hand Gesture Tracking Based on Improved Level Set Algorithm

DOI

10.2991/aiie-15.2015.12How to use a DOI?

Keywords

active contour; mean-shift algorithm; edge detection hand tracking

Abstract

The tracking and extraction the hand pose is the previous work of gesture analysis.I n this paper, a mixed Gauss model based level set contour extraction algorithm is presented. The algorithm combined with the mean shift algorithm to achieve the extraction of hand contour dynamically in a video sequence. This method first get the initial contour by color information, and build Gaussian model of the inside and outside of the outline of the image features by using Gaussian mixture model.Depending on the characteristics of the Gaussian distribution and combining with active contour algorithm for image segmentation,then obtaining hand movement position by mean shift algorithm, we achieved gesture tracking.The test results show that compared to pixel-based active contour algorithm, this method has greater stability, which can get more accurate extraction region and achieve accurate contour extraction and gesture tracking.

Copyright

© 2015, 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/).

Download article (PDF)

TY  - CONF
AU  - N.G. Yu
AU  - M. Guo
AU  - F.F. Mo
AU  - X.G. Ruan
PY  - 2015/07
DA  - 2015/07
TI  - Hand Gesture Tracking Based on Improved Level Set Algorithm
BT  - Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering
PB  - Atlantis Press
SP  - 41
EP  - 44
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-15.2015.12
DO  - 10.2991/aiie-15.2015.12
ID  - Yu2015/07
ER  -