{"title":"图像数据假设检验的统计基础","authors":"Kanatani K.","doi":"10.1006/ciun.1994.1064","DOIUrl":null,"url":null,"abstract":"<div><p>A statistical foundation is given to the problem of hypothesizing and testing geometric properties of image data heuristically derived by Kanatani (<em>CVGIP: Image Understanding</em><em>54</em> (1991), 333-348). Points and lines in the image are represented by \"N-vectors\" and their reliability is evaluated by their \"covariance matrices\". Under a Gaussian approximation of the distribution, the test takes the form of a χ<sup>2</sup> test. Test criteria are explicitly stated for model matching and testing edge groupings, vanishing points, focuses of expansion, and vanishing lines.</p></div>","PeriodicalId":100350,"journal":{"name":"CVGIP: Image Understanding","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1994-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1006/ciun.1994.1064","citationCount":"5","resultStr":"{\"title\":\"Statistical Foundation for Hypothesis Testing of Image Data\",\"authors\":\"Kanatani K.\",\"doi\":\"10.1006/ciun.1994.1064\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>A statistical foundation is given to the problem of hypothesizing and testing geometric properties of image data heuristically derived by Kanatani (<em>CVGIP: Image Understanding</em><em>54</em> (1991), 333-348). Points and lines in the image are represented by \\\"N-vectors\\\" and their reliability is evaluated by their \\\"covariance matrices\\\". Under a Gaussian approximation of the distribution, the test takes the form of a χ<sup>2</sup> test. Test criteria are explicitly stated for model matching and testing edge groupings, vanishing points, focuses of expansion, and vanishing lines.</p></div>\",\"PeriodicalId\":100350,\"journal\":{\"name\":\"CVGIP: Image Understanding\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1006/ciun.1994.1064\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CVGIP: Image Understanding\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1049966084710643\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"CVGIP: Image Understanding","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1049966084710643","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Statistical Foundation for Hypothesis Testing of Image Data
A statistical foundation is given to the problem of hypothesizing and testing geometric properties of image data heuristically derived by Kanatani (CVGIP: Image Understanding54 (1991), 333-348). Points and lines in the image are represented by "N-vectors" and their reliability is evaluated by their "covariance matrices". Under a Gaussian approximation of the distribution, the test takes the form of a χ2 test. Test criteria are explicitly stated for model matching and testing edge groupings, vanishing points, focuses of expansion, and vanishing lines.
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