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This paper proposes a novel data fusion approach to attack this problem, which combines an entropy-based Canny (EC) operator with the local and global optical flow (LGOF) method, namely EC-LGOF. Its operation contains four steps. The EC operator firstly computes the contour of moving objects in a video sequence, and the LGOF method then establishes the motion vector field. Thirdly, the minimum error threshold selection (METS) method is employed to distinguish the moving object from the background. Finally, edge information fuses temporal information concerning the optic flow to label the moving objects. Experiments are conducted and the results are given to show the feasibility and effectiveness of the proposed method.<\/jats:p>","DOI":"10.1177\/0142331218773550","type":"journal-article","created":{"date-parts":[[2018,6,6]],"date-time":"2018-06-06T18:17:14Z","timestamp":1528309034000},"page":"793-804","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":6,"title":["Real-time detection of moving objects in a video sequence by using data fusion algorithm"],"prefix":"10.1177","volume":"41","author":[{"given":"Chao","family":"Tang","sequence":"first","affiliation":[{"name":"Department of Computer Science and Technology, Hefei University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huosheng","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Electronic Engineering, University of Essex, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5765-2278","authenticated-orcid":false,"given":"Miaohui","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Energy, Jiangxi Academy of Sciences, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wen-Jian","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer and Information Technology, Shanxi University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiao-Feng","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Hefei University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Feng","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Computer and Information Technology, Shanxi University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer and Information Engineering, Xiamen University of Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2018,6,6]]},"reference":[{"key":"bibr1-0142331218773550","volume-title":"1st International Workshop on Pattern Recognition","author":"Al-Smadi MM","year":"2016"},{"key":"bibr2-0142331218773550","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-011-9301-3"},{"key":"bibr3-0142331218773550","doi-asserted-by":"publisher","DOI":"10.1109\/IADCC.2015.7154719"},{"key":"bibr4-0142331218773550","doi-asserted-by":"publisher","DOI":"10.1023\/B:VISI.0000045324.43199.43"},{"key":"bibr5-0142331218773550","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2014.2298377"},{"key":"bibr6-0142331218773550","unstructured":"Fisher R (2001) CAVIAR: Context Aware Vision using Image-based Active Recognition. 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