Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/25494
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dc.contributor.authorWan Khairunizam, Wan Ahmad-
dc.contributor.authorMohd Azri, Abdul Aziz-
dc.contributor.authorShahriman, Abu Bakar-
dc.contributor.authorSiti Khadijah, Zaaba-
dc.contributor.authorZuwairie, Ibrahim-
dc.contributor.authorZulkifli, Md Yusof-
dc.contributor.authorIsmail, Ibrahim-
dc.contributor.authorJameel Abdulla, Ahmed Mukred-
dc.contributor.authorN. Mokhtar-
dc.date.accessioned2013-05-16T01:39:27Z-
dc.date.available2013-05-16T01:39:27Z-
dc.date.issued2012-06-30-
dc.identifier.citationAdvanced Science Letters, vol.13 (1), 2012 , pages 534-539en_US
dc.identifier.issn1936-6612-
dc.identifier.urihttp://dx.doi.org/10.1166/asl.2012.3953-
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/25494-
dc.descriptionLink to publisher's homepage at http://www.ingentaconnect.com/content/asp/aslen_US
dc.description.abstractIn 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.en_US
dc.language.isoenen_US
dc.publisherAmerican Scientific Publishersen_US
dc.subjectGesture recognitionen_US
dc.subjectHuman motion measurementen_US
dc.subjectMotion capture systemen_US
dc.subject3D motionen_US
dc.subjectUpper body motionen_US
dc.titleProbability Distribution of Arm Trajectory for Motion Estimation and Gesture Recognitionen_US
dc.typeArticleen_US
Appears in Collections:School of Mechatronic Engineering (Articles)
Shahriman Abu Bakar, Assoc. Prof. Ir. Ts. Dr.
Ismail Ibrahim
Siti Khadijah Za'aba, Assoc. Prof. Ts. Dr.

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