Probability distribution of arm trajectory for motion estimation and gesture recognition
Document Type
Article
Publication Date
1-1-2012
Abstract
In the human motion measurement, motion capture system is used to record the movement of the human body by using different types of sensors such as a magnetic position sensor, a mechanical motion detector and a vision sensor. The most challenging task in human motion measurement is to achieve the ability and reliability of a motion capture system for tracking and recognizing dynamic gestures, because human body structure has many degrees of freedom. This paper introduces a 3D motion measurement of the human upper body by using an optical motion capture system for the purpose of the estimation of human upper body motions, which is based on the probability distribution of arm trajectories. In this study, by examining the characteristic of the arm trajectory, motion features are selected and classified by using the fuzzy technique. The posture of the occluded body part is probabilistically estimated by using the aggregation of the fuzzy information of arm trajectories and the constructed human upper body model. Experimental results show that the use of the system effectively works for classifying various motion patterns and estimating the occluded posture in the motion.
Keywords
Arm trajectory Estimation Fuzzy technique Gesture Upper body model
Divisions
fac_eng
Publication Title
Advanced Science Letters
Volume
13
Issue
1
Publisher
Advanced Science Letters
Additional Information
Export Date: 28 January 2013 Source: Scopus Language of Original Document: English Correspondence Address: Wan, K.; School of Mechatronic Engineering, Universiti Malaysia Perlis, Main Campus Ulu Pauh, 02600 Perlis, Malaysia References: Zhanli, H., Na, Z., Yang, L., Jianbao, G., Junyan, R., Qiyang, Z., Hairong, Z., (2011) Advanced Science Letters, 4, p. 2; Manresa, C., Varona, J., Mas, R., Perales, F.J., (2005) Electronic Letters on Computer Vision and Image Analysis, 5, p. 3; Stephan, J.J., Khudayer, S., (2010) International Journal of Advancements in Computing Technology, 2, p. 4; Kirishima, T., Manabe, Y., Sato, K., Chihara, K., (2010) Journal on Image and Video Processing, 10; Gutemberg, B., Guerra, F., (2005) Journal of Theoretical and Applied Informatics, 9, p. 2; Sigal, L., Balan, A., Black, M.J., Huang, J., (2010) International Journal of Computer Vision, 87, p. 1; Miyata, N., Kouchi, M., Kurihara, T., Mochimaru, M., (2004) International Conference on Intelligent Robots and Systems, , (eds.), Sendai, Japan, September-October; Butalia, A., Shah, D., Dharaskar, R.V., (2010) International Journal of Computer Applications, 1, p. 5; Manigandan, M., Jackin, I.M., (2010) International Conference on Advances in Computer Engineering, , (eds.), Bangalore, India, June; Gunes, H., Piccardi, M., (2007) Journal of Network and Computer Applications, 30, p. 4; Bevilacqua, F., Guédy, F., Schnell, N., Fléty, E., Leroy, N., (2007) International conference on New Interfaces For Musical Expression, , Eds., New York, USA, June; Sawada, H., Ukegawa, T., Benoit, E., (2004) International Workshop on Fuzzy Systems and Innovational Computing, , (eds.), Kitakyusyu, Japan, June; Wan, K., Sawada, H., (2008) International Conference on Mechatronics and Automation, , (eds.), Takamatsu, Japan, August; Wan, K., Sawada, H., (2009) SICE Journal of Control, Measurement and System Integration, 2, p. 5; Zadeh, L.A., Klir, G.J., Yuan, B., (1996) Fuzzy Sets, Fuzzy Logic, and Fuzzy Systems, , (eds.), World Scientific, Singapore