{"title":"从日常生活场景中发现对象实例","authors":"Hongwen Kang, M. Hebert, T. Kanade","doi":"10.1109/ICCV.2011.6126314","DOIUrl":null,"url":null,"abstract":"We propose an approach to identify and segment objects from scenes that a person (or robot) encounters in Activities of Daily Living (ADL). Images collected in those cluttered scenes contain multiple objects. Each image provides only a partial, possibly very different view of each object. An object instance discovery program must be able to link pieces of visual information from multiple images and extract the consistent patterns.","PeriodicalId":6391,"journal":{"name":"2011 International Conference on Computer Vision","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"61","resultStr":"{\"title\":\"Discovering object instances from scenes of Daily Living\",\"authors\":\"Hongwen Kang, M. Hebert, T. Kanade\",\"doi\":\"10.1109/ICCV.2011.6126314\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose an approach to identify and segment objects from scenes that a person (or robot) encounters in Activities of Daily Living (ADL). Images collected in those cluttered scenes contain multiple objects. Each image provides only a partial, possibly very different view of each object. An object instance discovery program must be able to link pieces of visual information from multiple images and extract the consistent patterns.\",\"PeriodicalId\":6391,\"journal\":{\"name\":\"2011 International Conference on Computer Vision\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"61\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Computer Vision\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCV.2011.6126314\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Computer Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCV.2011.6126314","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Discovering object instances from scenes of Daily Living
We propose an approach to identify and segment objects from scenes that a person (or robot) encounters in Activities of Daily Living (ADL). Images collected in those cluttered scenes contain multiple objects. Each image provides only a partial, possibly very different view of each object. An object instance discovery program must be able to link pieces of visual information from multiple images and extract the consistent patterns.
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