By Topic

An Automatic Hand Gesture Recognition System Based on Viola-Jones Method and SVMs

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Liu Yun ; Coll. of Inf. Sci. & Technol., Qingdao Univ. of Sci. & Technol., Qingdao, China ; Zhang Peng

In this paper we present an automatic hand gesture recognition system operating on video stream. The system consists of two modules: hand gesture detection module and hand gesture recognition module. The detection module could accurately locate the hand regions with a blue rectangle; this is mainly based on Viola-Jones method, which is currently considered the fastest and most accurate learning-based method for object detection. In the recognition module, the Hu invariant moments feature vectors of the detected hand gesture are extracted and a support vector machines (SVMs) classifier is trained for final recognition, due to its high generalization performance without the need to add a priori knowledge. The performance of the proposed system is tested through a series of experiments and a simple human-computer interaction application based on hand gesture recognition method is finally developed.

Published in:

Computer Science and Engineering, 2009. WCSE '09. Second International Workshop on  (Volume:2 )

Date of Conference:

28-30 Oct. 2009