Affiliations: Department of Computer Science Engineering, Jaypee Institute of Information Technology, Noida, Uttar Pradesh, India
Correspondence:
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Corresponding author: Yogesh Chandra Tewari, Department of Computer Science Engineering, Jaypee Institute of Information Technology, Noida, Uttar Pradesh, India. E-mail:tewari.yogi@yahoo.in
Abstract: In this paper, we introduce a hand gesture
recognition system to recognize real time gesture in unconstrained
environment. We consider fixed set of manual commands, and develop a simple,
yet affective procedure for gesture recognition. The system consists of
three modules: real time hand tracking, gesture set training and gesture
recognition. We have used Viola Jones Object detection framework which
employs a variant of the learning algorithm AdaBoost to both select the best
features and to train classifiers that use them. We have tested our system
vocabulary of four gestures and results effectiveness of this approach using
principal component analysis and Eigen vectors.
Keywords: ASL, gesture recognition, HAAR, hand tracking, PCA, Eigen vector
