{"title":"动态纹理的分割","authors":"A. Rahman, M. Murshed","doi":"10.1109/ICCITECHN.2007.4579388","DOIUrl":null,"url":null,"abstract":"Dynamic textures are textures with motion. Characterization of visual processes consisting of multiple dynamic textures is of vital importance to computer vision research, with a diverse set of applications in the field of robot navigation, and remote monitoring applications etc. In the current literature, however, studies are mostly limited to characterization of single dynamic textures. In this paper we aim to address the problem of segmenting image sequences consisting of multiple dynamic textures. More precisely we separate image segments having different characteristic motion patterns - a key attribute of individual dynamic textures. Experimental results demonstrate the ability of the proposed technique by segmenting a wide variety of multiple dynamic texture image sequences.","PeriodicalId":338170,"journal":{"name":"2007 10th international conference on computer and information technology","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Segmentation of dynamic textures\",\"authors\":\"A. Rahman, M. Murshed\",\"doi\":\"10.1109/ICCITECHN.2007.4579388\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Dynamic textures are textures with motion. Characterization of visual processes consisting of multiple dynamic textures is of vital importance to computer vision research, with a diverse set of applications in the field of robot navigation, and remote monitoring applications etc. In the current literature, however, studies are mostly limited to characterization of single dynamic textures. In this paper we aim to address the problem of segmenting image sequences consisting of multiple dynamic textures. More precisely we separate image segments having different characteristic motion patterns - a key attribute of individual dynamic textures. Experimental results demonstrate the ability of the proposed technique by segmenting a wide variety of multiple dynamic texture image sequences.\",\"PeriodicalId\":338170,\"journal\":{\"name\":\"2007 10th international conference on computer and information technology\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 10th international conference on computer and information technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCITECHN.2007.4579388\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 10th international conference on computer and information technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCITECHN.2007.4579388","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dynamic textures are textures with motion. Characterization of visual processes consisting of multiple dynamic textures is of vital importance to computer vision research, with a diverse set of applications in the field of robot navigation, and remote monitoring applications etc. In the current literature, however, studies are mostly limited to characterization of single dynamic textures. In this paper we aim to address the problem of segmenting image sequences consisting of multiple dynamic textures. More precisely we separate image segments having different characteristic motion patterns - a key attribute of individual dynamic textures. Experimental results demonstrate the ability of the proposed technique by segmenting a wide variety of multiple dynamic texture image sequences.