TY - GEN
T1 - Estimation of human behaviors based on human actions using an ANN
AU - Maierdan, Maimaitimin
AU - Watanabe, Keigo
AU - Maeyama, Shoichi
N1 - Publisher Copyright:
© 2014 Institute of Control, Robotics and Systems (ICROS).
PY - 2014/12/16
Y1 - 2014/12/16
N2 - An approach to human behavior recognition is presented in this paper. The system is separated into two parts: human action recognition and object recognition. The estimation result is composed of a simple action 'Pointing' and a virtual assumed object, which has two attributes, one is 'current status' and the other is 'acceptable behavior'. Once the human action and object are recognized, then detect whether a vector calculated by human elbow intersected the object. If the vector is intersected, then estimate human behavior by combining the human action and the object attribute. The artificial neural network (ANN) is discussed as a main part of the current research. Whole ANN processing is simulated by Octave 3.8, the human actions are captured by Microsoft Kinect, and a human model is built by using human joint data.
AB - An approach to human behavior recognition is presented in this paper. The system is separated into two parts: human action recognition and object recognition. The estimation result is composed of a simple action 'Pointing' and a virtual assumed object, which has two attributes, one is 'current status' and the other is 'acceptable behavior'. Once the human action and object are recognized, then detect whether a vector calculated by human elbow intersected the object. If the vector is intersected, then estimate human behavior by combining the human action and the object attribute. The artificial neural network (ANN) is discussed as a main part of the current research. Whole ANN processing is simulated by Octave 3.8, the human actions are captured by Microsoft Kinect, and a human model is built by using human joint data.
KW - Artificial neural network
KW - Human action recognition
KW - Human behavior recognition
KW - Object attribute
UR - http://www.scopus.com/inward/record.url?scp=84920169678&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84920169678&partnerID=8YFLogxK
U2 - 10.1109/ICCAS.2014.6987965
DO - 10.1109/ICCAS.2014.6987965
M3 - Conference contribution
AN - SCOPUS:84920169678
T3 - International Conference on Control, Automation and Systems
SP - 94
EP - 98
BT - International Conference on Control, Automation and Systems
PB - IEEE Computer Society
T2 - 2014 14th International Conference on Control, Automation and Systems, ICCAS 2014
Y2 - 22 October 2014 through 25 October 2014
ER -