{"title":"基于二进制特征的图像检索，具有有效的索引和评分","authors":"Yusuke Uchida, S. Sakazawa, S. Satoh","doi":"10.1109/GCCE.2014.7031244","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a stand-alone mobile visual search system based on binary features and bag of visual words framework. The contribution of this paper is two-fold: (1) a visual word-dependent substring extraction method is proposed; (2) a modified version of the local NBNN scoring method is proposed in the context of image retrieval. The proposed system improves retrieval accuracy by 11% compared with a conventional method without increasing the database size.","PeriodicalId":145771,"journal":{"name":"2014 IEEE 3rd Global Conference on Consumer Electronics (GCCE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Binary feature-based image retrieval with effective indexing and scoring\",\"authors\":\"Yusuke Uchida, S. Sakazawa, S. Satoh\",\"doi\":\"10.1109/GCCE.2014.7031244\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a stand-alone mobile visual search system based on binary features and bag of visual words framework. The contribution of this paper is two-fold: (1) a visual word-dependent substring extraction method is proposed; (2) a modified version of the local NBNN scoring method is proposed in the context of image retrieval. The proposed system improves retrieval accuracy by 11% compared with a conventional method without increasing the database size.\",\"PeriodicalId\":145771,\"journal\":{\"name\":\"2014 IEEE 3rd Global Conference on Consumer Electronics (GCCE)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE 3rd Global Conference on Consumer Electronics (GCCE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GCCE.2014.7031244\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 3rd Global Conference on Consumer Electronics (GCCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GCCE.2014.7031244","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Binary feature-based image retrieval with effective indexing and scoring
In this paper, we propose a stand-alone mobile visual search system based on binary features and bag of visual words framework. The contribution of this paper is two-fold: (1) a visual word-dependent substring extraction method is proposed; (2) a modified version of the local NBNN scoring method is proposed in the context of image retrieval. The proposed system improves retrieval accuracy by 11% compared with a conventional method without increasing the database size.
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