Appearance Based Recognition Methodology for Recognising Fingerspelling Alphabets
Abstract
In this paper, a study on the suitability of an appearance based model, specifically PCA based model, for the purpose of recognising fingerspel-ling (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.
Cite
Text
Suraj and Guru. "Appearance Based Recognition Methodology for Recognising Fingerspelling Alphabets." International Joint Conference on Artificial Intelligence, 2007.Markdown
[Suraj and Guru. "Appearance Based Recognition Methodology for Recognising Fingerspelling Alphabets." International Joint Conference on Artificial Intelligence, 2007.](https://mlanthology.org/ijcai/2007/suraj2007ijcai-appearance/)BibTeX
@inproceedings{suraj2007ijcai-appearance,
title = {{Appearance Based Recognition Methodology for Recognising Fingerspelling Alphabets}},
author = {Suraj, M. G. and Guru, D. S.},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2007},
pages = {605-610},
url = {https://mlanthology.org/ijcai/2007/suraj2007ijcai-appearance/}
}