{"title":"基于图像矩的物体结构与跟踪","authors":"Lourena Rocha, L. Velho, P. Carvalho","doi":"10.1109/SIBGRA.2002.1167130","DOIUrl":null,"url":null,"abstract":"This paper presents a new method for structuring and tracking of objects in video sequences. Our approach is based on image moments and the BSP-tree data structure. We use invariant properties of these moments to construct a BSP-tree and determine an ellipsis that approximates the object's shape. Then, we employ this information to track objects frame by frame through the image sequence. The method works well for segmented images with a single object and we assume that the motion will not change abruptly.","PeriodicalId":286814,"journal":{"name":"Proceedings. XV Brazilian Symposium on Computer Graphics and Image Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"52","resultStr":"{\"title\":\"Image moments-based structuring and tracking of objects\",\"authors\":\"Lourena Rocha, L. Velho, P. Carvalho\",\"doi\":\"10.1109/SIBGRA.2002.1167130\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a new method for structuring and tracking of objects in video sequences. Our approach is based on image moments and the BSP-tree data structure. We use invariant properties of these moments to construct a BSP-tree and determine an ellipsis that approximates the object's shape. Then, we employ this information to track objects frame by frame through the image sequence. The method works well for segmented images with a single object and we assume that the motion will not change abruptly.\",\"PeriodicalId\":286814,\"journal\":{\"name\":\"Proceedings. XV Brazilian Symposium on Computer Graphics and Image Processing\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-10-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"52\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. XV Brazilian Symposium on Computer Graphics and Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIBGRA.2002.1167130\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. XV Brazilian Symposium on Computer Graphics and Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIBGRA.2002.1167130","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Image moments-based structuring and tracking of objects
This paper presents a new method for structuring and tracking of objects in video sequences. Our approach is based on image moments and the BSP-tree data structure. We use invariant properties of these moments to construct a BSP-tree and determine an ellipsis that approximates the object's shape. Then, we employ this information to track objects frame by frame through the image sequence. The method works well for segmented images with a single object and we assume that the motion will not change abruptly.
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