Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/13119
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dc.contributor.authorPattamaset S.
dc.contributor.authorCharoenpong T.
dc.contributor.authorCharoenpong P.
dc.contributor.authorChianrabutra C.
dc.date.accessioned2021-04-05T03:22:22Z-
dc.date.available2021-04-05T03:22:22Z-
dc.date.issued2017
dc.identifier.other2-s2.0-85017505310
dc.identifier.urihttps://ir.swu.ac.th/jspui/handle/123456789/13119-
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85017505310&doi=10.1109%2fKST.2017.7886075&partnerID=40&md5=542ed48053145805f0f1cb1e569fdd3d
dc.description.abstractDue to a problem of current research occurring when detecting a human falling in a camera direction, we propose a new method for detecting human fall detection by using body vector technique. This method consists of three steps. Two image sequence is used as the input of the system. Firstly markers are affixed on sixteen joints. These markers are extracted by using mahalanobis distance. Secondly, the stereo vision technique is used to construct human joints in three dimensional space. Finally, joint coordinates are used to compute principal component vector. Human falling is detected from an angle between the human body vector and the vertical axis and the human center velocity. To test the performance of the proposed method, subject walks to the cameras. Falling down in the camera direction by twenty subjects is used. Accuracy is 100%. This method perform effectively for detecting human falling in the camera direction. © 2017 IEEE.
dc.subjectCameras
dc.subjectPrincipal component analysis
dc.subjectStereo image processing
dc.subjectStereo vision
dc.subjectFalling protection
dc.subjectHuman fall detection
dc.subjectJoint coordinates
dc.subjectMahalanobis distances
dc.subjectPrincipal Components
dc.subjectThree dimensional space
dc.subjectVector techniques
dc.subjectVision technique
dc.subjectVectors
dc.titleHuman fall detection by using the body vector
dc.typeConference Paper
dc.rights.holderScopus
dc.identifier.bibliograpycitation2017 9th International Conference on Knowledge and Smart Technology: Crunching Information of Everything, KST 2017. (2017), p.162-165
dc.identifier.doi10.1109/KST.2017.7886075
Appears in Collections:Scopus 1983-2021

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