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Gesture recognition for fingerspelling applications.
- Source :
- ACM SIGACCESS Conference on Computers & Accessibility; Jan2010, p261-262, 2p
- Publication Year :
- 2010
-
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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- Database :
- Complementary Index
- Journal :
- ACM SIGACCESS Conference on Computers & Accessibility
- Publication Type :
- Conference
- Accession number :
- 89072543
- Full Text :
- https://doi.org/10.1145/1878803.1878861