{"title":"透视不变角度排序","authors":"David Shaw, N. Barnes","doi":"10.1109/DICTA.2009.50","DOIUrl":null,"url":null,"abstract":"In this paper we present the geometric property of perspective invariant angle ordering; the order of angles between point features. We describe how this can be used to exploit the structure of the appearance of features on planar or near planar surfaces to improve precision for localisation and object recognition. We show test results on real-world images that show marked improvement over straight bag-of-features approaches.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"96 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Perspective Invariant Angle Ordering\",\"authors\":\"David Shaw, N. Barnes\",\"doi\":\"10.1109/DICTA.2009.50\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we present the geometric property of perspective invariant angle ordering; the order of angles between point features. We describe how this can be used to exploit the structure of the appearance of features on planar or near planar surfaces to improve precision for localisation and object recognition. We show test results on real-world images that show marked improvement over straight bag-of-features approaches.\",\"PeriodicalId\":277395,\"journal\":{\"name\":\"2009 Digital Image Computing: Techniques and Applications\",\"volume\":\"96 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Digital Image Computing: Techniques and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DICTA.2009.50\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Digital Image Computing: Techniques and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DICTA.2009.50","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper we present the geometric property of perspective invariant angle ordering; the order of angles between point features. We describe how this can be used to exploit the structure of the appearance of features on planar or near planar surfaces to improve precision for localisation and object recognition. We show test results on real-world images that show marked improvement over straight bag-of-features approaches.
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