{"title":"使用草图查询的交互式视频资产检索","authors":"Stuart James, J. Collomosse","doi":"10.1145/2668904.2668940","DOIUrl":null,"url":null,"abstract":"We present a new algorithm for searching video repositories using free-hand sketches. Our queries express both appearance (color, shape) and motion attributes, as well as semantic properties (object labels) enabling hybrid queries to be specified. Unlike existing sketch based video retrieval (SBVR) systems that enable hybrid queries of this form, we do not adopt a model fitting/optimization approach to match at query-time. Rather, we create an efficiently searchable index via a novel space-time descriptor that encapsulates all these properties. The real-time performance yielded by our indexing approach enables interactive refinement of search results within a relevance feedback (RF) framework; a unique contribution to SBVR. We evaluate our system over 700 sports footage clips exhibiting a variety of clutter and motion conditions, demonstrating significant accuracy and speed gains over the state of the art.","PeriodicalId":401915,"journal":{"name":"Proceedings of the 11th European Conference on Visual Media Production","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Interactive video asset retrieval using sketched queries\",\"authors\":\"Stuart James, J. Collomosse\",\"doi\":\"10.1145/2668904.2668940\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a new algorithm for searching video repositories using free-hand sketches. Our queries express both appearance (color, shape) and motion attributes, as well as semantic properties (object labels) enabling hybrid queries to be specified. Unlike existing sketch based video retrieval (SBVR) systems that enable hybrid queries of this form, we do not adopt a model fitting/optimization approach to match at query-time. Rather, we create an efficiently searchable index via a novel space-time descriptor that encapsulates all these properties. The real-time performance yielded by our indexing approach enables interactive refinement of search results within a relevance feedback (RF) framework; a unique contribution to SBVR. We evaluate our system over 700 sports footage clips exhibiting a variety of clutter and motion conditions, demonstrating significant accuracy and speed gains over the state of the art.\",\"PeriodicalId\":401915,\"journal\":{\"name\":\"Proceedings of the 11th European Conference on Visual Media Production\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 11th European Conference on Visual Media Production\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2668904.2668940\",\"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 of the 11th European Conference on Visual Media Production","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2668904.2668940","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Interactive video asset retrieval using sketched queries
We present a new algorithm for searching video repositories using free-hand sketches. Our queries express both appearance (color, shape) and motion attributes, as well as semantic properties (object labels) enabling hybrid queries to be specified. Unlike existing sketch based video retrieval (SBVR) systems that enable hybrid queries of this form, we do not adopt a model fitting/optimization approach to match at query-time. Rather, we create an efficiently searchable index via a novel space-time descriptor that encapsulates all these properties. The real-time performance yielded by our indexing approach enables interactive refinement of search results within a relevance feedback (RF) framework; a unique contribution to SBVR. We evaluate our system over 700 sports footage clips exhibiting a variety of clutter and motion conditions, demonstrating significant accuracy and speed gains over the state of the art.