Paper Info
Title
Gabor filter-based hand-pose angle estimation for hand gesture recognition under varying illumination
Abstract
In this paper, we present a novel approach for hand gesture recognition based on Gabor filters and support vector machine (SVM) classifiers for environments with varying illumination. The proposed method (1) is robust against varying illumination, which is achieved using an adaptive skin-color model switching method; (2) is insensitive to hand-pose variations, which is achieved using a Gabor filter-based gesture angle estimation and correction method; (3) allows users to wear either a long- or short-sleeve shirt, which is achieved using a method that segments the hand from the forearm. To evaluate the robustness of the proposed method, we created a database of hand gestures in realistic conditions. A recognition rate of 96.1% was achieved using the proposed method. A dynamic gesture recognition system is also presented for real-life conditions. In the proposed system, the recognition results improved from 72.8% to 93.7% when the hand-pose correction module was used, indicating that using the responses of Gabor filters to estimate the hand-pose angle is effective.
Year
DOI
Venue
2011
10.1016/j.eswa.2010.11.016
Expert Syst. Appl.
Keywords
Field
DocType
hand-pose angle estimation,varying illumination,dynamic gesture recognition system,correction method,recognition result,gabor filter,hand gesture recognition,gabor filter-based gesture angle,recognition rate,proposed system,support vector machine (svm),principal component analysis (pca),gesture recognition,support vector machine,principal component analysis
Computer vision,Pattern recognition,Gesture,Computer science,Support vector machine,Gesture recognition,Robustness (computer science),Gabor filter,Artificial intelligence
Journal
Volume
Issue
ISSN
38
5
Expert Systems With Applications
Citations 
PageRank 
References 
31
1.10
12
Authors
3
Name
Order
Citations
PageRank
Deng-Yuan Huang116315.28
Wu-Chih Hu224427.01
Sung-Hsiang Chang3512.14