{"title":"改进的智能剪刀和自适应跳帧视频对象分割","authors":"Yang Gaobo , Yu Shengfa","doi":"10.1016/j.rti.2005.06.005","DOIUrl":null,"url":null,"abstract":"<div><p>MPEG-4 introduces the concept of video object to support content-based functionalities. Video object segmentation is a crucial step for object-based coding and manipulation. In this paper, a robust semi- automatic video object segmentation scheme is proposed. To efficiently and accurately define the initial object contour<span>, modified intelligent scissors is proposed on the basis of original intelligent scissors. It can improve about 6–8 times the processing speed with only slight sacrifice of accuracy, which just meets the requirements of initial object extraction for semi-automatic approach. To avoid errors accumulating and propagating during object tracking, an adaptive frame skipping scheme is proposed to decompose video sequence into video clips. For rigid and non-rigid video objects, two different image segmentation<span> algorithms are utilized, and then region-based backward projection technique is adopted to interpolate the video object plane (VOPs) of other frames within every video clip. The proposed approach can cope with occlusion/disocclusion problem to most extent. Experimental results demonstrate the effectiveness and robustness of the method.</span></span></p></div>","PeriodicalId":101062,"journal":{"name":"Real-Time Imaging","volume":"11 4","pages":"Pages 310-322"},"PeriodicalIF":0.0000,"publicationDate":"2005-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.rti.2005.06.005","citationCount":"8","resultStr":"{\"title\":\"Modified intelligent scissors and adaptive frame skipping for video object segmentation\",\"authors\":\"Yang Gaobo , Yu Shengfa\",\"doi\":\"10.1016/j.rti.2005.06.005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>MPEG-4 introduces the concept of video object to support content-based functionalities. Video object segmentation is a crucial step for object-based coding and manipulation. In this paper, a robust semi- automatic video object segmentation scheme is proposed. To efficiently and accurately define the initial object contour<span>, modified intelligent scissors is proposed on the basis of original intelligent scissors. It can improve about 6–8 times the processing speed with only slight sacrifice of accuracy, which just meets the requirements of initial object extraction for semi-automatic approach. To avoid errors accumulating and propagating during object tracking, an adaptive frame skipping scheme is proposed to decompose video sequence into video clips. For rigid and non-rigid video objects, two different image segmentation<span> algorithms are utilized, and then region-based backward projection technique is adopted to interpolate the video object plane (VOPs) of other frames within every video clip. The proposed approach can cope with occlusion/disocclusion problem to most extent. Experimental results demonstrate the effectiveness and robustness of the method.</span></span></p></div>\",\"PeriodicalId\":101062,\"journal\":{\"name\":\"Real-Time Imaging\",\"volume\":\"11 4\",\"pages\":\"Pages 310-322\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.rti.2005.06.005\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Real-Time Imaging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1077201405000458\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Real-Time Imaging","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1077201405000458","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modified intelligent scissors and adaptive frame skipping for video object segmentation
MPEG-4 introduces the concept of video object to support content-based functionalities. Video object segmentation is a crucial step for object-based coding and manipulation. In this paper, a robust semi- automatic video object segmentation scheme is proposed. To efficiently and accurately define the initial object contour, modified intelligent scissors is proposed on the basis of original intelligent scissors. It can improve about 6–8 times the processing speed with only slight sacrifice of accuracy, which just meets the requirements of initial object extraction for semi-automatic approach. To avoid errors accumulating and propagating during object tracking, an adaptive frame skipping scheme is proposed to decompose video sequence into video clips. For rigid and non-rigid video objects, two different image segmentation algorithms are utilized, and then region-based backward projection technique is adopted to interpolate the video object plane (VOPs) of other frames within every video clip. The proposed approach can cope with occlusion/disocclusion problem to most extent. Experimental results demonstrate the effectiveness and robustness of the method.