Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/3525
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dc.contributor.authorSheshadri, Manasa Gowri Hebbur-
dc.contributor.authorOkade, Manish-
dc.date.accessioned2020-03-05T11:57:20Z-
dc.date.available2020-03-05T11:57:20Z-
dc.date.issued2020-02-
dc.identifier.citationTwenty Sixth National Conference on Communications, IIT Kharagpur, 21-23 February 202en_US
dc.identifier.urihttp://hdl.handle.net/2080/3525-
dc.descriptionCopyright belongs to proceedings publisheren_US
dc.description.abstractRecognizing humans through gait has been an em-anant biometric technology in the recent years owing to the fact that it is unobtrusive since it does not require a subject’s coop-eration. This paper investigates Kinect based gait recognition of human subjects for surveillance applications especially in narrow corridor and airport scenarios where only the frontal views are available. Two features namely skeleton size feature and projectile motion feature extracted from skeleton data and one feature derived by segmenting the depth data using superpixels followed by SURF descriptor extraction are utilized in a hierarchical framework to obtain the closest matching subject for recognition purposes. The proposed method provides considerable increase in the recognition accuracy and recognition rank in comparison to state-of-the-art gait recognition approaches.en_US
dc.subjectHuman Gaiten_US
dc.subjectKinect cameraen_US
dc.subjectSkeleton dataen_US
dc.subjectDepth dataen_US
dc.subjectFrontal Gaiten_US
dc.subjectkNN Classifieren_US
dc.titleKinect Based Frontal Gait Recognition Using Skeleton and Depth Derived Featuresen_US
dc.typeArticleen_US
Appears in Collections:Conference Papers

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