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dc.contributor.authorLiu, JSen_US
dc.contributor.authorChuang, JHen_US
dc.date.accessioned2014-12-08T15:42:57Z-
dc.date.available2014-12-08T15:42:57Z-
dc.date.issued2002-01-01en_US
dc.identifier.issn0031-3203en_US
dc.identifier.urihttp://dx.doi.org/10.1016/S0031-3203(00)00174-6en_US
dc.identifier.urihttp://hdl.handle.net/11536/29099-
dc.description.abstractFor choosing specific cross-ratios as 2D projective coordinates in various computer vision applications, a reasonable error analysis model is usually required. This investigation adopts the assumption of normal distribution for positioning errors of point features in an image to formulate the error variances of cross-ratios. Based on a geometry-based error analysis, a straightforward way of identifying the cross-ratios with minimum error variances is proposed. Simulation results show that the proposed approach. as well as a further simplified alternative, yield much better estimations of minimum error variances in terms of accuracy, cost, and stability compared with some other methods, e.g., the one based on the rule given by Georis et al. (IEEE Trans. Pattern Anal. Mach. Intell. 20 (4) (1998) 366). Some causes of the performance differences in the estimations are explained using a special configuration of point features. (C) 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjecterror analysisen_US
dc.subjectcross-ratioen_US
dc.subjectcomputer visionen_US
dc.subject3D reconstructionen_US
dc.titleA geometry-based error estimation for cross-ratiosen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/S0031-3203(00)00174-6en_US
dc.identifier.journalPATTERN RECOGNITIONen_US
dc.citation.volume35en_US
dc.citation.issue1en_US
dc.citation.spage155en_US
dc.citation.epage167en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000172435800014-
dc.citation.woscount4-
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