Hand Gesture Recognition Using Object Based Key Frame Selection

Abstract

The sign language recognition is the most popular research area involving computer vision, pattern recognition and image processing. It enhances communication capabilities of the mute person. In this paper, we present an object based key frame selection. Hausdorff distance and Euclidean distance are used for shape similarity for hand gesture recognition. We proposed the use of nonlinear time alignment model with key frame selection facility and gesture trajectory features for hand gesture recognition. Experimental results demonstrate the effectiveness of our proposed scheme for recognizing American Sign Language.