A real-time hand gesture recognition method

Author

Zhao, Yafei ; Wang, Weidong ; Wang, Yuehai

Author_Institution

Inst. of Inf. & Commun. Eng., Zhejiang Univ., Hangzhou, China

fYear

2011

fDate

9-11 Sept. 2011

Firstpage

2475

Lastpage

2478

Abstract

This paper presents a real-time hand gesture recognition method. Hand regions are located by combining adaptive skin color detection and motion detection. Histograms of oriented gradients (HOG) are used to describe hand image. Extracted HOG features are projected into low-dimensional subspace using PCA-LDA (Principle Component Analysis and Linear Discriminant Analysis). And then distances between the projected features and each gesture class center are calculated. Finally the recognition results are obtained by the nearest neighbor method. Experimental results showed that the proposed method gained detection rate up to 91% with real-time performance.

Keywords

feature extraction; gesture recognition; image colour analysis; image motion analysis; principal component analysis; PCA-LDA; adaptive skin color detection; detection rate; extracted features; gesture class center; hand image; histograms of oriented gradients; linear discriminant analysis; low-dimensional subspace; motion detection; nearest neighbor method; principle component analysis; real-time hand gesture recognition method; Feature extraction; Gesture recognition; Histograms; Image color analysis; Motion detection; Real time systems; Skin; PCA-LDA; hand gesture recognition; histogram of oriented gradients; motion detection; nearest neighbor; real-time; skin detetion;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronics, Communications and Control (ICECC), 2011 International Conference on

Conference_Location

Ningbo

Print_ISBN

978-1-4577-0320-1

Type

conf

DOI

10.1109/ICECC.2011.6066597

Filename

6066597