{"created":"2020-08-25T17:29:05.870488+00:00","id":3047,"links":{},"metadata":{"_buckets":{"deposit":"28227565-67ca-4e2d-8594-ef8679ff9eaf"},"_deposit":{"created_by":45,"id":"3047","owner":"45","owners":[45],"owners_ext":{"displayname":"","email":"dimennyaung@uit.edu.mm","username":""},"pid":{"revision_id":0,"type":"recid","value":"3047"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/3047","sets":["1582963342780:1596102355557"]},"communities":["uit"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Background Subtraction and Foreground Detection based on Codebook Model with Kalman Filter","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"Foreground object extraction is an important\nsubject for computer vision applications. The\nseparation of foreground objects form the\nbackground is the crucial step in application\nsuch as video surveillance. In order to extract\nforeground object from a video scene, a\nbackground model which can represent dynamic\nchanges in the scene is required. A robust,\naccurate and high performance approach is still\na great challenge today. In this paper, the\nbackground modeling approach based on\nCodebook model with Kalman Filter is\npresented. This approach can be used to extract\nforeground objects from the video stream. The\nLab color space is used in this approach to\ncalculate color difference between two pixels\nusing CIEDE2000 color difference formula.\nExtracted foreground object from video sequence\nusing this approach is useful for object detection\nin video surveillance applications."}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value_mlt":[{"interim":"Object Detection"}]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2020-08-25"}],"displaytype":"preview","filename":"Background Subtraction and Foreground Detection based on Codebook Model with Kalman Filter.pdf","filesize":[{"value":"362 Kb"}],"format":"application/pdf","licensetype":"license_0","url":{"url":"https://meral.edu.mm/record/3047/files/Background Subtraction and Foreground Detection based on Codebook Model with Kalman Filter.pdf"},"version_id":"2e9783d5-0f13-4d4e-8a8c-88bb0caed308"}]},"item_1583103147082":{"attribute_name":"Conference papers","attribute_value_mlt":[{"subitem_acronym":"ICCA 2017","subitem_c_date":"16-17 February, 2017","subitem_conference_title":"15th International Conference on Computer Applications","subitem_place":"Sedona Hotel, Yangon, Myanmar","subitem_website":"https://www.ucsy.edu.mm/page227.do"}]},"item_1583105942107":{"attribute_name":"Authors","attribute_value_mlt":[{"subitem_authors":[{"subitem_authors_fullname":"Su Su Aung"},{"subitem_authors_fullname":"Zin Mar Kyu"}]}]},"item_1583108359239":{"attribute_name":"Upload type","attribute_value_mlt":[{"interim":"Publication"}]},"item_1583108428133":{"attribute_name":"Publication type","attribute_value_mlt":[{"interim":"Conference paper"}]},"item_1583159729339":{"attribute_name":"Publication date","attribute_value":"2017-02-17"},"item_title":"Background Subtraction and Foreground Detection based on Codebook Model with Kalman Filter","item_type_id":"21","owner":"45","path":["1596102355557"],"publish_date":"2020-08-25","publish_status":"0","recid":"3047","relation_version_is_last":true,"title":["Background Subtraction and Foreground Detection based on Codebook Model with Kalman Filter"],"weko_creator_id":"45","weko_shared_id":-1},"updated":"2021-12-13T07:58:34.595050+00:00"}