TY - GEN
T1 - Modeling of the chasing behaviors for developmental program of children with autism spectrum disorders
AU - Tsuji, Airi
AU - Sekine, Satoru
AU - Enomoto, Takuya
AU - Matsuda, Soichiro
AU - Yamamoto, Junichi
AU - Suzuki, Kenji
N1 - Funding Information:
This study was supported by JST-CRESTʠ Social Imaging for All Children’s Education Supporting Creative Activities and Facilitating Social Interaction. ʡ
Publisher Copyright:
© 2017 IEEE.
PY - 2017/11/14
Y1 - 2017/11/14
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85040568695&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85040568695&partnerID=8YFLogxK
U2 - 10.1109/ICCI-CC.2017.8109739
DO - 10.1109/ICCI-CC.2017.8109739
M3 - Conference contribution
AN - SCOPUS:85040568695
T3 - Proceedings of 2017 IEEE 16th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017
SP - 115
EP - 120
BT - Proceedings of 2017 IEEE 16th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017
A2 - Wang, Yingxu
A2 - Hamdy, Freddie
A2 - Howard, Newton
A2 - Zadeh, Lotfi A.
A2 - Hussain, Amir
A2 - Widrow, Bernard
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 16th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017
Y2 - 26 July 2017 through 28 July 2017
ER -