{"created":"2020-09-01T10:08:06.491192+00:00","id":3422,"links":{},"metadata":{"_buckets":{"deposit":"d6842e9a-b542-4feb-8774-69ef5ca2424b"},"_deposit":{"id":"3422","owners":[],"pid":{"revision_id":0,"type":"recid","value":"3422"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/3422","sets":["1582963302567:1597824273898"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Geometric Kinect Joints Computing for Human Fall Recognition","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"This paper proposes an computing analysis onhuman geometric shape features to detect a fallbehavior. The system mainly computes the changeson human orientation (torso angle) and centroidheight via the human skeleton joints extracted byKinect sensor. The system computes and tracks thespatial changes of these human orientation andcentroid height and distinguishs a fall behavioramong other daily activities by using a thresholdingalgorithm. The main objective of this computation isto minize the computational time and to increase thetrue alarms in developing a fall detection. The systemworks the feature extraction on our collected falldetection dataset containing the fall data along withdaily activities such as sitting down, lying, combing.Standing, etc., are collected by Microsoft Kinectsensor."}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value_mlt":[{"interim":"Fall Detection"},{"interim":"Image Processing"},{"interim":"Skeleton Joint Extraction"},{"interim":"Geometric Computing"},{"interim":"Microsoft Kinect Sensor"}]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2019-07-22"}],"displaytype":"preview","filename":"ICCA 2019 Proceedings Book-pages-100-105.pdf","filesize":[{"value":"604 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/3422/files/ICCA 2019 Proceedings Book-pages-100-105.pdf"},"version_id":"34b20308-6d0e-4c86-a34a-94f4c992c378"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_issue":"","subitem_journal_title":"Seventeenth International Conference on Computer Applications(ICCA 2019)","subitem_pages":"","subitem_volume":""}]},"item_1583103147082":{"attribute_name":"Conference papers","attribute_value_mlt":[{"subitem_acronym":"","subitem_c_date":"","subitem_conference_title":"","subitem_part":"","subitem_place":"","subitem_session":"","subitem_website":""}]},"item_1583103211336":{"attribute_name":"Books/reports/chapters","attribute_value_mlt":[{"subitem_book_title":"","subitem_isbn":"","subitem_pages":"","subitem_place":"","subitem_publisher":""}]},"item_1583103233624":{"attribute_name":"Thesis/dissertations","attribute_value_mlt":[{"subitem_awarding_university":"","subitem_supervisor(s)":[{"subitem_supervisor":""}]}]},"item_1583105942107":{"attribute_name":"Authors","attribute_value_mlt":[{"subitem_authors":[{"subitem_authors_fullname":"Htoo, Chit Kyin"},{"subitem_authors_fullname":"Sein, Myint Myint"}]}]},"item_1583108359239":{"attribute_name":"Upload type","attribute_value_mlt":[{"interim":"Publication"}]},"item_1583108428133":{"attribute_name":"Publication type","attribute_value_mlt":[{"interim":"Article"}]},"item_1583159729339":{"attribute_name":"Publication date","attribute_value":"2019-02-27"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"http://onlineresource.ucsy.edu.mm/handle/123456789/1175"},"item_title":"Geometric Kinect Joints Computing for Human Fall Recognition","item_type_id":"21","owner":"1","path":["1597824273898"],"publish_date":"2019-07-22","publish_status":"0","recid":"3422","relation_version_is_last":true,"title":["Geometric Kinect Joints Computing for Human Fall Recognition"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T06:06:23.816375+00:00"}