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ICMI
2003
Springer

Large vocabulary sign language recognition based on hierarchical decision trees

9 years 2 months ago
Large vocabulary sign language recognition based on hierarchical decision trees
The major difficulty for large vocabulary sign language or gesture recognition lies in the huge search space due to a variety of recognized classes. How to reduce the recognition time without loss of accuracy is a challenge issue. In this paper, a hierarchical decision tree is first presented for large vocabulary sign language recognition based on the divide-and-conquer principle. As each sign feature has the different importance to gestures, the corresponding classifiers are proposed for the hierarchical decision to gesture attributes. One- or two- handed classifier with little computational cost is first used to eliminate many impossible candidates. The subsequent hand shape classifier is performed on the possible candidate space. SOFM/HMM classifier is employed to get the final results at the last non-leaf nodes that only include few candidates. Experimental results on a large vocabulary of 5113-signs show that the proposed method drastically reduces the recognition time by 11 time...
Gaolin Fang, Wen Gao, Debin Zhao
Added 07 Jul 2010
Updated 07 Jul 2010
Type Conference
Year 2003
Where ICMI
Authors Gaolin Fang, Wen Gao, Debin Zhao
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