Renata C. B. Madeo
ABSTRACT
This paper presents an approach for carrying out gesture recognition for the Brazilian Sign Language Manual Alphabet. The gestural patterns are treated as a combination of three primitives, or cheremes - hand configuration, hand orientation and hand movement. The recognizer is built in a modular architecture composed by inductive reasoning modules, which use the artificial neural network Fuzzy Learning Vector Quantization; and rule-based modules. This architecture has been tested and results are presented here. Some strengths of such approach are: robustness of recognition, portability to similar contexts, extensibility of the dataset to be recognize and reduction of the vocabulary recognition problem to the recognition of its primitives.
- D. B. Dias, R. C. B. Madeo, T. Rocha, H. H. Bíscaro, and S. M. Peres. Hand movement recognition for brazilian sign language: A study using distance-based neural networks. In International Joint Conference on Neural Networks, pages 697--704. IEEE, 2009. Google Scholar
Digital Library
- R. C. B. Madeo, S. M. Peres, H. H. Bíscaro, D. B. Dias, and C. Boscarioli. A committee machine implementing the pattern recognition module for fingerspelling applications. In Proceedings of the 25th Annual ACM Symposium on Applied Computing 2010, pages 954--958. ACM Press, 2010. Google ScholarDigital Library
- S. Mitra and T. Acharya. Gesture recognition: A survey. IEEE Trans. on Systems, Man, and Cybernetics - Part C, 37(3), May 2007. Google ScholarDigital Library
- D. J. Sturman and D. Zelter. A survey of glove-based input. IEEE Computer Graphics and Applications, 14:30--39, January 1994. Google ScholarDigital Library
- C. Vogler and D. N. Metaxas. Toward scalability in ASL recognition: Breaking down signs into phonemes. In GW'99: Proceedings of the International Gesture Workshop on Gesture-Based Communication in Human-Computer Interaction, pages 211--224, London, UK, 1999. Springer-Verlag. Google ScholarDigital Library
Index Terms
- Gesture recognition for fingerspelling applications: an approach based on sign language cheremes
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