TY - GEN
T1 - Recognition of manipulation sequences by human hand based on Support Vector Machine
AU - Matsuo, Kazuya
AU - Murakami, Kouji
AU - Hasegawa, Tsutomu
AU - Kurazume, Ryo
PY - 2007
Y1 - 2007
N2 - This paper describes a method of recognizing a manual task executed by a human hand by using the Support Vector Machine (SVM). We define several task states which are segmented from the continuous motion of human fingers in the context of an object manipulation. Based on margins of SVMs, the method constructs a binary decision tree which most effectively classifies and symbolizes the task state from joint angle trajectories of human fingers as input. The binary decision tree constructed by our method has been evaluated through experiments of recognizing the task states during a valve manipulation.
AB - This paper describes a method of recognizing a manual task executed by a human hand by using the Support Vector Machine (SVM). We define several task states which are segmented from the continuous motion of human fingers in the context of an object manipulation. Based on margins of SVMs, the method constructs a binary decision tree which most effectively classifies and symbolizes the task state from joint angle trajectories of human fingers as input. The binary decision tree constructed by our method has been evaluated through experiments of recognizing the task states during a valve manipulation.
UR - http://www.scopus.com/inward/record.url?scp=49949101046&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=49949101046&partnerID=8YFLogxK
U2 - 10.1109/IECON.2007.4460099
DO - 10.1109/IECON.2007.4460099
M3 - Conference contribution
AN - SCOPUS:49949101046
SN - 1424407834
SN - 9781424407835
T3 - IECON Proceedings (Industrial Electronics Conference)
SP - 2801
EP - 2806
BT - Proceedings of the 33rd Annual Conference of the IEEE Industrial Electronics Society, IECON
T2 - 33rd Annual Conference of the IEEE Industrial Electronics Society, IECON
Y2 - 5 November 2007 through 8 November 2007
ER -