A Segmentation Method for Sign Language Recognition
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Information Vol.E78-D No.1 pp.49-57
- Publication Date
- 1995/01/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- PAPER
- Category
- Image Processing, Computer Graphics and Pattern Recognition
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Eiji OHIRA, Hirohiko SAGAWA, Tomoko SAKIYAMA, Masaru OHKI, "A Segmentation Method for Sign Language Recognition" in IEICE TRANSACTIONS on Information,
vol. E78-D, no. 1, pp. 49-57, January 1995, doi: .
Abstract: 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.
URL: https://global.ieice.org/en_transactions/information/10.1587/e78-d_1_49/_p
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@ARTICLE{e78-d_1_49,
author={Eiji OHIRA, Hirohiko SAGAWA, Tomoko SAKIYAMA, Masaru OHKI, },
journal={IEICE TRANSACTIONS on Information},
title={A Segmentation Method for Sign Language Recognition},
year={1995},
volume={E78-D},
number={1},
pages={49-57},
abstract={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.},
keywords={},
doi={},
ISSN={},
month={January},}
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TY - JOUR
TI - A Segmentation Method for Sign Language Recognition
T2 - IEICE TRANSACTIONS on Information
SP - 49
EP - 57
AU - Eiji OHIRA
AU - Hirohiko SAGAWA
AU - Tomoko SAKIYAMA
AU - Masaru OHKI
PY - 1995
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E78-D
IS - 1
JA - IEICE TRANSACTIONS on Information
Y1 - January 1995
AB - 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.
ER -
English
