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2017 IEEE 16th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC) (2017)
Oxford, United Kingdom
July 26, 2017 to July 28, 2017
ISBN: 978-1-5386-0772-5
pp: 115-120
Airi Tsuji , University of Tsukuba, 1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan
Satoru Sekine , Keio University, 2-15-45 Mita, Minato-ku, Tokyo 108-8345, Japan
Takuya Enomoto , Keio University, 2-15-45 Mita, Minato-ku, Tokyo 108-8345, Japan
Soichiro Matsuda , University of Tsukuba, 1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan
Junichi Yamamoto , Keio University, 2-15-45 Mita, Minato-ku, Tokyo 108-8345, Japan
Kenji Suzuki , University of Tsukuba, 1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan
ABSTRACT
We are researching and developing dynamic interpersonal distance models and real-time recognition systems for the social development training therapy of children with autism spectrum disorders (ASD). In particular, we modeled the quantitative measurements of chasing behaviors observed during therapy. Chasing behaviors are a highly social activity because children need to predict the movement of a partner (therapist). In order to measure these behaviors, the video coding using observational method by experts is needed but it is very time consuming. We consider that establishing models for real-time automated recognition of chasing behavior supports social skills development programs for children with ASD. This study focuses on chasing behavior and presents experimental results for recognition of chasing behavior during actual therapy. The proposed system reveals that it is possible to extract tracking behaviors which closely agree with therapist observations.
INDEX TERMS
Observers, Medical treatment, Electronic mail, Psychology, Atmospheric measurements, Particle measurements, Cameras
CITATION

A. Tsuji, S. Sekine, T. Enomoto, S. Matsuda, J. Yamamoto and K. Suzuki, "Modeling of the chasing behaviors for developmental program of children with autism spectrum disorders," 2017 IEEE 16th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC), Oxford, United Kingdom, 2017, pp. 115-120.
doi:10.1109/ICCI-CC.2017.8109739
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