A Segmentation Method for Sign Language Recognition

Eiji OHIRA  Hirohiko SAGAWA  Tomoko SAKIYAMA  Masaru OHKI  

IEICE TRANSACTIONS on Information and Systems   Vol.E78-D   No.1   pp.49-57
Publication Date: 1995/01/25
Online ISSN: 
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Image Processing, Computer Graphics and Pattern Recognition
sign language,  recognition,  segmentation,  

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This paper discusses sign word segmentation methods and extraction of motion features for sign language recognition. Because Japanese sign language grammar has not yet been systematized and because sign language does not have prepositions, it is more difficult to use grammar and meaning information in sign language recognition than in speech recognition. Segmentation significantly improves recognition efficiency, so we propose a method of dividing sign language based on rests and on the envelope and minimum of motion speed. The sign unit corresponding to a sign word is detected based on the divided position using such features as the change of hand shape. Experiments confirmed the validity of word segmentation of sign language based on the temporal structure of motion.