Appearance Based Recognition Methodology for Recognising Fingerspelling Alphabets
Proceedings of the Twentieth International Joint Conference on Artificial Intelligence. Pages 605-609.
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.
@inproceedings{ijcai2007p96,
title = {Appearance Based Recognition Methodology for Recognising Fingerspelling Alphabets},
author = {Suraj, M. G. and Guru, D. S.},
booktitle = {Proceedings of the Twentieth International Joint Conference on
Artificial Intelligence, {IJCAI-07}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Ramon López de Mántaras},
pages = {605--609},
year = {2007},
url = {https://ijcai.org/proceedings/2007/96},
}
TY - CPAPER TI - Appearance Based Recognition Methodology for Recognising Fingerspelling Alphabets AU - Suraj, M. G. AU - Guru, D. S. T2 - Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07 PB - International Joint Conferences on Artificial Intelligence PY - 2007 SP - 605 EP - 609 UR - https://ijcai.org/proceedings/2007/96 ER -Copied
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