Kun Li, Qionghai Dai, Wenli Xu, Jingyu Yang, Jianmin Jiang
{"title":"三维运动估计通过矩阵完成。","authors":"Kun Li, Qionghai Dai, Wenli Xu, Jingyu Yang, Jianmin Jiang","doi":"10.1109/TSMCB.2011.2168953","DOIUrl":null,"url":null,"abstract":"<p><p>Three-dimensional motion estimation from multiview video sequences is of vital importance to achieve high-quality dynamic scene reconstruction. In this paper, we propose a new 3-D motion estimation method based on matrix completion. Taking a reconstructed 3-D mesh as the underlying scene representation, this method automatically estimates motions of 3-D objects. A \"separating + merging\" framework is introduced to multiview 3-D motion estimation. In the separating step, initial motions are first estimated for each view with a neighboring view. Then, in the merging step, the motions obtained by each view are merged together and optimized by low-rank matrix completion method. The most accurate motion estimation for each vertex in the recovered matrix is further selected by three spatiotemporal criteria. Experimental results on data sets with synthetic motions and real motions show that our method can reliably estimate 3-D motions.</p>","PeriodicalId":55006,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TSMCB.2011.2168953","citationCount":"17","resultStr":"{\"title\":\"Three-dimensional motion estimation via matrix completion.\",\"authors\":\"Kun Li, Qionghai Dai, Wenli Xu, Jingyu Yang, Jianmin Jiang\",\"doi\":\"10.1109/TSMCB.2011.2168953\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Three-dimensional motion estimation from multiview video sequences is of vital importance to achieve high-quality dynamic scene reconstruction. In this paper, we propose a new 3-D motion estimation method based on matrix completion. Taking a reconstructed 3-D mesh as the underlying scene representation, this method automatically estimates motions of 3-D objects. A \\\"separating + merging\\\" framework is introduced to multiview 3-D motion estimation. In the separating step, initial motions are first estimated for each view with a neighboring view. Then, in the merging step, the motions obtained by each view are merged together and optimized by low-rank matrix completion method. The most accurate motion estimation for each vertex in the recovered matrix is further selected by three spatiotemporal criteria. Experimental results on data sets with synthetic motions and real motions show that our method can reliably estimate 3-D motions.</p>\",\"PeriodicalId\":55006,\"journal\":{\"name\":\"IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1109/TSMCB.2011.2168953\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TSMCB.2011.2168953\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2011/10/14 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TSMCB.2011.2168953","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2011/10/14 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
Three-dimensional motion estimation via matrix completion.
Three-dimensional motion estimation from multiview video sequences is of vital importance to achieve high-quality dynamic scene reconstruction. In this paper, we propose a new 3-D motion estimation method based on matrix completion. Taking a reconstructed 3-D mesh as the underlying scene representation, this method automatically estimates motions of 3-D objects. A "separating + merging" framework is introduced to multiview 3-D motion estimation. In the separating step, initial motions are first estimated for each view with a neighboring view. Then, in the merging step, the motions obtained by each view are merged together and optimized by low-rank matrix completion method. The most accurate motion estimation for each vertex in the recovered matrix is further selected by three spatiotemporal criteria. Experimental results on data sets with synthetic motions and real motions show that our method can reliably estimate 3-D motions.