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A Vision-Based Method for Recognizing Non-manual Information in Japanese Sign Language

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Book cover Advances in Multimodal Interfaces — ICMI 2000 (ICMI 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1948))

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Abstract

This paper describes a vision-based method for recognizing the non- manual information in Japanese Sign Language (JSL). This new modality information provides grammatical constraints useful for JSL word segmentation and interpretation. Our attention is focused on head motion, the most dominant non-manual information in JSL. We designed an interactive color-modeling scheme for robust face detection. Two video cameras are vertically arranged to take the frontal and profile image of the JSL user, and head motions are classified into eleven patterns. Moment-based feature and statistical motion feature are adopted to represent these motion patterns. Classification of the motion features is performed with linear discrimant analysis method. Initial experimental results show that the method has good recognition rate and can be realized in real-time.

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References

  1. M. Takeuchi and H. Sagawa, “Sign Language Recognition Method Based On Spatial Information and Multimodal Sign Language Database”, RWCP Symposium, June 9-10, 1998, pp.193–198.

    Google Scholar 

  2. M-H. Yang, N. Ahuja, and D. Kriegman, “Face Detection Using Mixtures of Linear Subspaces”, International Conference on Face and Gesture, March 2000.

    Google Scholar 

  3. W. Skarbek and A. Koschan, “Colour Image Segmentation, A Survey”, Technical Report of Technical University of Berlin, October 1994.

    Google Scholar 

  4. M. Xu and T. Akatsuka, “Multi-module method for detection of human face from complex background”, Proceeding of SPIE Conference on Applications of Digital Image Processing, Vol. 3460, pp.793–802, 1998.

    Google Scholar 

  5. J.K. Aggarwal and Q. Cai, “Human Motion Analysis: A Review”, Computer Vision and Image Understanding, Vol.73, No.3, March pp.428–440, 1999.

    Article  Google Scholar 

  6. Mubarak Shah and Ramesh Jain(Eds.), “Motion-Based Recognition”, Kluwer Academic Publishers 1998.

    Google Scholar 

  7. Bisser Raytchev, Osamu Hassegawa, Nobuyuki Otsu, “User-independent online gesture recognition by relative motion extraction”, Pattern Recognition Letters, Jan. 2000, PP.69–82.

    Google Scholar 

  8. H. Sagawa and M. Takeuchi, “A Method for Recognizing a Sequence of Sign Language, Words Represented in a Japanese Sign Language Sentence”, International Conference on Face and Gesture, March 2000.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Electrotechnical Laboratory (ETL), Umezono 1-1-4, 305-8568, Tsukuba City, Ibaraki, Japan

    Ming Xu, Bisser Raytchev, Katsuhiko Sakaue & Osamu Hasegawa

  2. RWCP Multi-modal Functions Hitachi Laboratory 1-280, Higashi-koigakubo, 185-8601, Kokubunji-shi, Tokyo, Japan

    Atsuko Koizumi, Masaru Takeuchi & Hirohiko Sagawa

Authors
  1. Ming Xu
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  2. Bisser Raytchev
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  3. Katsuhiko Sakaue
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  4. Osamu Hasegawa
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  5. Atsuko Koizumi
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  6. Masaru Takeuchi
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  7. Hirohiko Sagawa
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Editor information

Editors and Affiliations

  1. Institute of Automation, Chinese Academy of Sciences, P.O.Box 2728, 100080, Beijing, China

    Tieniu Tan

  2. Computer Department, Media Laboratory, Tsinghua University, 100084, Beijing, China

    Yuanchun Shi

  3. Institute of Computing Technology, Chinese Academy of Sciences, P.O.Box 2704, 100080, Beijing, China

    Wen Gao

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© 2000 Springer-Verlag Berlin Heidelberg

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Xu, M. et al. (2000). A Vision-Based Method for Recognizing Non-manual Information in Japanese Sign Language. In: Tan, T., Shi, Y., Gao, W. (eds) Advances in Multimodal Interfaces — ICMI 2000. ICMI 2000. Lecture Notes in Computer Science, vol 1948. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-40063-X_75

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  • DOI: https://doi.org/10.1007/3-540-40063-X_75

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41180-2

  • Online ISBN: 978-3-540-40063-9

  • eBook Packages: Springer Book Archive

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