Thai Sign Language Translation Using Fuzzy C-Means and Scale Invariant Feature Transform

Authors:
Suwannee Phitakwinai;Sansanee Auephanwiriyakul;Nipon Theera-Umpon
Affiliations:
Computer Engineering Department, Faculty of Engineering, Biomedical Engineering Center, Chiang Mai University, Chiang Mai, Thailand 50200;Computer Engineering Department, Faculty of Engineering, Biomedical Engineering Center, Chiang Mai University, Chiang Mai, Thailand 50200;Electrical Engineering Department, Faculty of Engineering, Biomedical Engineering Center, Chiang Mai University, Chiang Mai, Thailand 50200
Venue:
ICCSA '08 Proceedings of the international conference on Computational Science and Its Applications, Part II
Year:
2008

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Thai sign language translation using Scale Invariant Feature Transform and Hidden Markov Models

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Abstract

Visual communication is important for a deft and/or mute person. It is also one of the tools for the communication between human and machines. In this paper, we develop an automatic Thai finger-spelling sign language translation system using Fuzzy C-Means (FCM) and Scale Invariant Feature Transform (SIFT) algorithms. We collect key frames from several subjects at different times of day and for several days. We also collect testing Thai finger-spelling words video from 4 subjects. The system achieves 79.90% and 51.17% correct alphabet translation and the correct word translation, respectively, with the SIFT threshold of 0.7 and 1 nearest neighbor prototype. However, when we change the number of nearest neighbor prototypes to 3, the system yields 82.19% and 55.08% correct alphabet and correct word translation, respectively, at the same SIFT threshold. These results are comparable with the manually-picked Rframe translation system.