Mejda Chihaoui, Akram Elkefi, W. Bellil, C. Ben Amar
{"title":"Detection and Tracking of the Moving Objects in a Video Sequence by Geodesic Active Contour","authors":"Mejda Chihaoui, Akram Elkefi, W. Bellil, C. Ben Amar","doi":"10.1109/CGIV.2016.48","DOIUrl":null,"url":null,"abstract":"Detection of objects motion in image sequences is one of the most discussed research subjects in the artificial vision. In this paper, we propose a new approach for the detection and tracking of one or more objects in video sequences. Our proposed approach is based on geodesic active contour. In fact, the methods used in this domain generally rely on the detection by the geometric shapes that still have the isolated pixels constraints, i.e. they present a difficulty of extracting only the moving object and they do not generally allow detecting each object separately. For this, our approach reduces these constraints by initially dividing the video into a succession of images. The active contour is, then, applied to each image till the end of the sequence. Finally, we reconstruct these new video images containing moving objects detected by the geodesic active contour.","PeriodicalId":351561,"journal":{"name":"2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CGIV.2016.48","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Detection of objects motion in image sequences is one of the most discussed research subjects in the artificial vision. In this paper, we propose a new approach for the detection and tracking of one or more objects in video sequences. Our proposed approach is based on geodesic active contour. In fact, the methods used in this domain generally rely on the detection by the geometric shapes that still have the isolated pixels constraints, i.e. they present a difficulty of extracting only the moving object and they do not generally allow detecting each object separately. For this, our approach reduces these constraints by initially dividing the video into a succession of images. The active contour is, then, applied to each image till the end of the sequence. Finally, we reconstruct these new video images containing moving objects detected by the geodesic active contour.