TY - GEN
T1 - Gesture recognition based on spatiotemporal histogram of oriented gradient variation
AU - Kojima, Seiji
AU - Ohyama, Wataru
AU - Wakabayashi, Tetsushi
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - A fine-grained gesture recognition method based on spatiotemporal representation for cooking activities is proposed. Cooking is one of common housework activity in daily life. Supporting cooking using video-based gesture recognition can contribute to improve our quality of life. A cooking gesture recognition method which employs a spatiotemporal representation for both appearance of a cooker and surrounding kitchen utensils. Our proposed method employs Spatio-Temporal extension of Histogram of Oriented Gradient Variation (ST-HOGV) which can represent not only appearance and temporal change of independent objects but locations of these objects. Performance evaluation experiment using ACE dataset shows that recognition accuracy of 76.4% is obtained and the KSCGR evaluation score achieves 73.5%. While the proposed method does not require any a priori knowledge, the performance is comparative other gesture recognition method with a priori knowledge.
AB - A fine-grained gesture recognition method based on spatiotemporal representation for cooking activities is proposed. Cooking is one of common housework activity in daily life. Supporting cooking using video-based gesture recognition can contribute to improve our quality of life. A cooking gesture recognition method which employs a spatiotemporal representation for both appearance of a cooker and surrounding kitchen utensils. Our proposed method employs Spatio-Temporal extension of Histogram of Oriented Gradient Variation (ST-HOGV) which can represent not only appearance and temporal change of independent objects but locations of these objects. Performance evaluation experiment using ACE dataset shows that recognition accuracy of 76.4% is obtained and the KSCGR evaluation score achieves 73.5%. While the proposed method does not require any a priori knowledge, the performance is comparative other gesture recognition method with a priori knowledge.
UR - http://www.scopus.com/inward/record.url?scp=85051118758&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85051118758&partnerID=8YFLogxK
U2 - 10.1109/ICIEV.2017.8338581
DO - 10.1109/ICIEV.2017.8338581
M3 - Conference contribution
AN - SCOPUS:85051118758
T3 - 2017 6th International Conference on Informatics, Electronics and Vision and 2017 7th International Symposium in Computational Medical and Health Technology, ICIEV-ISCMHT 2017
SP - 1
EP - 4
BT - 2017 6th International Conference on Informatics, Electronics and Vision and 2017 7th International Symposium in Computational Medical and Health Technology, ICIEV-ISCMHT 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th International Conference on Informatics, Electronics and Vision and 2017 7th International Symposium in Computational Medical and Health Technology, ICIEV-ISCMHT 2017
Y2 - 1 September 2017 through 3 September 2017
ER -