Mechanical Feature Attributes for Modeling and Pattern Classification of Physical Activities
A rigorous investigation on the synergy of mechanical attributes to engineer tactics for measuring human activity in terms of forces, as well as to provide independency and discrimination clarity of action recognition using linear and non-linear classification methodologies from data mining and evolutionary computation, are the main objectives where this paper focuses on. Mechanical analysis is employed to mathematically describe and model human movement by using a number of mechanical features inspired mainly from Kinematics Dynamics. Such features employ a twofold role on the descriptive analysis of an activity, initially to provide statistics regarding inertial expressions, probable hazard levels, body-status of energy loss, and finally to exploit these attributes by decomposing the 3D time series data for pattern recognition in terms of actions and behaviours. The performance statistics are being utilized by a mobile robot for remote surveillance within a smart environment.
Theodoros Theodoridis Alexandros Agapitos Huosheng Hu Simon M. Lucas
Department of Computer Science,University of Essex Wivenhoe Park,Colchester CO4 3SQ,U.K.
国际会议
2009 IEEE International Conference on Information and Automation(2009年 IEEE信息与自动化国际学术会议)
珠海、澳门
英文
528-533
2009-06-22（万方平台首次上网日期，不代表论文的发表时间）