{"title":"一种新的语义视频分类模型","authors":"Wei Ren, M. Singh, S. Singh","doi":"10.1109/IPTA.2008.4743749","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a novel spatio-temporal video retrieval model to extract spatio-temporal attributes for semantic video category classification using high-level reasoning of video objects and scenes. We also explore the semantic logical inference learning of video attributes based on interpreting camera movements and object spatial constraints, as well the views on temporal continuity of video. We have used Minerva international video benchmark for the analysis of our algorithm.","PeriodicalId":384072,"journal":{"name":"2008 First Workshops on Image Processing Theory, Tools and Applications","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Novel Semantic Video Classification Model\",\"authors\":\"Wei Ren, M. Singh, S. Singh\",\"doi\":\"10.1109/IPTA.2008.4743749\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a novel spatio-temporal video retrieval model to extract spatio-temporal attributes for semantic video category classification using high-level reasoning of video objects and scenes. We also explore the semantic logical inference learning of video attributes based on interpreting camera movements and object spatial constraints, as well the views on temporal continuity of video. We have used Minerva international video benchmark for the analysis of our algorithm.\",\"PeriodicalId\":384072,\"journal\":{\"name\":\"2008 First Workshops on Image Processing Theory, Tools and Applications\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 First Workshops on Image Processing Theory, Tools and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IPTA.2008.4743749\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 First Workshops on Image Processing Theory, Tools and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPTA.2008.4743749","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we propose a novel spatio-temporal video retrieval model to extract spatio-temporal attributes for semantic video category classification using high-level reasoning of video objects and scenes. We also explore the semantic logical inference learning of video attributes based on interpreting camera movements and object spatial constraints, as well the views on temporal continuity of video. We have used Minerva international video benchmark for the analysis of our algorithm.