{"title":"序数措施的歧视性力量——朝向一个新的系数","authors":"S. Scherer, A. Pinz, P. Werth","doi":"10.1109/CVPR.1999.786920","DOIUrl":null,"url":null,"abstract":"Perspective distortion, occlusion and specular reflection are challenging problems in shape-from-stereo. In this paper we review one recently published area-based stereo matching algorithm (Bhat and Nayar, 1998) designed to be robust in these cases. Although the algorithm is an important contribution to stereo-matching, we show that its coefficient has a low discriminatory power, which leads to a significant number of multiple best matches. In order to cope with this drawback we introduce a new normalized ordinal correlation coefficient. Experiments showing the behavior of the proposed coefficient are performed on various datasets including real data with ground truth. The new coefficient reduces the occurrence of multiple best matches to almost zero per cent. It also shows a more robust and equally accurate behavior. These benefits are achieved at almost no additional computational costs.","PeriodicalId":20644,"journal":{"name":"Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149)","volume":"29 1","pages":"76-81 Vol. 1"},"PeriodicalIF":0.0000,"publicationDate":"1999-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":"{\"title\":\"The discriminatory power of ordinal measures - towards a new coefficient\",\"authors\":\"S. Scherer, A. Pinz, P. Werth\",\"doi\":\"10.1109/CVPR.1999.786920\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Perspective distortion, occlusion and specular reflection are challenging problems in shape-from-stereo. In this paper we review one recently published area-based stereo matching algorithm (Bhat and Nayar, 1998) designed to be robust in these cases. Although the algorithm is an important contribution to stereo-matching, we show that its coefficient has a low discriminatory power, which leads to a significant number of multiple best matches. In order to cope with this drawback we introduce a new normalized ordinal correlation coefficient. Experiments showing the behavior of the proposed coefficient are performed on various datasets including real data with ground truth. The new coefficient reduces the occurrence of multiple best matches to almost zero per cent. It also shows a more robust and equally accurate behavior. These benefits are achieved at almost no additional computational costs.\",\"PeriodicalId\":20644,\"journal\":{\"name\":\"Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149)\",\"volume\":\"29 1\",\"pages\":\"76-81 Vol. 1\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"23\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CVPR.1999.786920\",\"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. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVPR.1999.786920","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The discriminatory power of ordinal measures - towards a new coefficient
Perspective distortion, occlusion and specular reflection are challenging problems in shape-from-stereo. In this paper we review one recently published area-based stereo matching algorithm (Bhat and Nayar, 1998) designed to be robust in these cases. Although the algorithm is an important contribution to stereo-matching, we show that its coefficient has a low discriminatory power, which leads to a significant number of multiple best matches. In order to cope with this drawback we introduce a new normalized ordinal correlation coefficient. Experiments showing the behavior of the proposed coefficient are performed on various datasets including real data with ground truth. The new coefficient reduces the occurrence of multiple best matches to almost zero per cent. It also shows a more robust and equally accurate behavior. These benefits are achieved at almost no additional computational costs.