{"title":"对象分割和跟踪使用视频场所","authors":"J. Au, Ze-Nian Li, M. S. Drew","doi":"10.1109/ICPR.2002.1048360","DOIUrl":null,"url":null,"abstract":"In this paper, we present a new technique based on feature localization for segmenting and tracking objects in videos. A video locale is a sequence of image feature locales that share similar features (color, texture, shape, and motion) in the spatio-temporal domain of videos. Image feature locales are grown from tiles (blocks of pixels) and can be non-disjoint and non-connected. To exploit the temporal redundancy in digital videos, two algorithms (intra-frame and inter-frame) are used to grow locales efficiently. Multiple motion tracking is achieved by tracking and performing tile-based dominant motion estimation for each locale separately.","PeriodicalId":159502,"journal":{"name":"Object recognition supported by user interaction for service robots","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Object segmentation and tracking using video locales\",\"authors\":\"J. Au, Ze-Nian Li, M. S. Drew\",\"doi\":\"10.1109/ICPR.2002.1048360\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present a new technique based on feature localization for segmenting and tracking objects in videos. A video locale is a sequence of image feature locales that share similar features (color, texture, shape, and motion) in the spatio-temporal domain of videos. Image feature locales are grown from tiles (blocks of pixels) and can be non-disjoint and non-connected. To exploit the temporal redundancy in digital videos, two algorithms (intra-frame and inter-frame) are used to grow locales efficiently. Multiple motion tracking is achieved by tracking and performing tile-based dominant motion estimation for each locale separately.\",\"PeriodicalId\":159502,\"journal\":{\"name\":\"Object recognition supported by user interaction for service robots\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-12-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Object recognition supported by user interaction for service robots\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPR.2002.1048360\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Object recognition supported by user interaction for service robots","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPR.2002.1048360","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Object segmentation and tracking using video locales
In this paper, we present a new technique based on feature localization for segmenting and tracking objects in videos. A video locale is a sequence of image feature locales that share similar features (color, texture, shape, and motion) in the spatio-temporal domain of videos. Image feature locales are grown from tiles (blocks of pixels) and can be non-disjoint and non-connected. To exploit the temporal redundancy in digital videos, two algorithms (intra-frame and inter-frame) are used to grow locales efficiently. Multiple motion tracking is achieved by tracking and performing tile-based dominant motion estimation for each locale separately.