Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/12785
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dc.contributor.authorSombatpiboonporn P.
dc.contributor.authorCharoenpong P.
dc.contributor.authorCharoenpong T.
dc.date.accessioned2021-04-05T03:05:52Z-
dc.date.available2021-04-05T03:05:52Z-
dc.date.issued2018
dc.identifier.other2-s2.0-85053460208
dc.identifier.urihttps://ir.swu.ac.th/jspui/handle/123456789/12785-
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85053460208&doi=10.1109%2fICSEC.2017.8443945&partnerID=40&md5=c19459c671e701bdf3580d3ef33dad4c
dc.description.abstractSmart home is an alternative function in present accommodation. Many technologies are developed for smart home. Human gait recognition system for indoor area is applied for monitoring purpose such as elder health care system. However, simple and effective algorithm is necessary for real-world applications. In this paper, we propose a new method of human gait identification system for indoor area by using human joints projection and closest distance technique. The algorithm consists of four step: image sequence acquisition, human joints segmentation, human joints projection and gait recognition. Firstly, human 2D sequence image is acquired. Red nine markers are attached on human joints. Secondly, markers are extracted by color thresholding technique. Human joints are then tracked. Third, such joints is projected in a dimension. Finally, Euclidean distance technique is used to compare two 2D human points between test data and train data. Human gait is recognized by the closest distance. To evaluate the proposed method, fifteen subjects walk pass 2D camera in same one way. A subject was tested three time. Average accuracy rate is 95.55%. This method perform effectively. The advantages of this method over existing methods is simple algorithm and effective for small size of target as using in accommodation. © 2017 IEEE.
dc.subjectAutomation
dc.subjectGait analysis
dc.subjectHealth care
dc.subjectImage acquisition
dc.subjectImage segmentation
dc.subjectIntelligent buildings
dc.subjectColor thresholding
dc.subjectEffective algorithms
dc.subjectEuclidean distance
dc.subjectGait recognition
dc.subjectHealth-care system
dc.subjectHuman gait recognition
dc.subjectMonitoring purpose
dc.subjectSurveillance systems
dc.subjectPattern recognition
dc.titleA New Method of Gait Recognition by Human Joint Projection and Closest Distance Technique
dc.typeConference Paper
dc.rights.holderScopus
dc.identifier.bibliograpycitationICSEC 2017 - 21st International Computer Science and Engineering Conference 2017, Proceeding. (2018), p.89-92
dc.identifier.doi10.1109/ICSEC.2017.8443945
Appears in Collections:Scopus 1983-2021

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