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2009
Springer

Influence of Handshape Information on Automatic Sign Language Recognition

8 years 3 months ago
Influence of Handshape Information on Automatic Sign Language Recognition
Research on automatic sign language recognition (ASLR) has mostly been conducted from a machine learning perspective. We propose to implement results from human sign recognition studies in ASLR. In a previous study it was found that handshape is important for human sign recognition. The current paper describes the implementation of this conclusion: using handshape in ASLR. Handshape information in three different representations is added to an existing ASLR system. The results show that recognition improves, except for one representation. This refutes the idea that extra (handshape) information will always improve recognition. Results also vary per sign: some sign classifiers improve greatly, others are unaffected, and rare cases even show decreased performance. Adapting classifiers to specific sign types could be the key for future ASLR. Key words: sign language, automatic sign language recognition, handshape representation
Gineke A. ten Holt, Marcel J. T. Reinders, Emile A
Added 18 Feb 2011
Updated 18 Feb 2011
Type Journal
Year 2009
Where GW
Authors Gineke A. ten Holt, Marcel J. T. Reinders, Emile A. Hendriks, Huib de Ridder, Andrea J. van Doorn
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