Appearance based recognition methodology for recognising fingerspelling alphabets

Authors:
M. G. Suraj;D. S. Guru
Affiliations:
Department of Studies in Computer Science, University of Mysore, Mysore, India;Department of Studies in Computer Science, University of Mysore, Mysore, India
Venue:
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Year:
2007

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Abstract

In this paper, a study on the suitability of an appearance based model, specifically PCA based model, for the purpose of recognising fingerspelling (sign language) alphabets is made. Its recognition performance on a large and varied real time dataset is analysed. In order to enhance the performance of a PCA based model, we suggest to incorporate a sort of pre-processing operation both during training and recognition. An exhaustive experiment conducted on a large number of fingerspelling alphabet images taken from 20 different individuals in real environment has revealed that the suggested pre-processing has a drastic impact in improving the performance of a conventional PCA based model.