Please use this identifier to cite or link to this item: https://doi.org/10.1023/A:1008105012585
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dc.titleGeometry of distorted visual space and Cremona transformation
dc.contributor.authorCheong, L.-F.
dc.contributor.authorNg, K.-O.
dc.date.accessioned2014-06-17T06:49:06Z
dc.date.available2014-06-17T06:49:06Z
dc.date.issued1999
dc.identifier.citationCheong, L.-F., Ng, K.-O. (1999). Geometry of distorted visual space and Cremona transformation. International Journal of Computer Vision 32 (3) : 195-212. ScholarBank@NUS Repository. https://doi.org/10.1023/A:1008105012585
dc.identifier.issn09205691
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/62259
dc.description.abstractAn important issue concerning the design of any vision system is the choice of a proper space representation. In order to search for clues to a suitable representation, we look at the distortion of space arising from errors in motion or stereo estimates. Understanding this space distortion has important epistemological implications for the problem of space representation because it tells us what can be and what cannot be computed. This paper is therefore an enquiry into the nature of space representation through the study of the space distortion, though it is not a psychophysical or physiological study but rather a computational one. We show that the distortion transformation is a quadratic Cremona transformation, which is bijective almost everywhere except on the set of fundamental elements. We identify the fundamental elements of both the direct and the inverse transformations, and study the behaviour of the space distortion by analyzing the transformation of space elements (lines, planes) that pass through these fundamental elements.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1023/A:1008105012585
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentMATHEMATICS
dc.contributor.departmentELECTRICAL ENGINEERING
dc.description.doi10.1023/A:1008105012585
dc.description.sourcetitleInternational Journal of Computer Vision
dc.description.volume32
dc.description.issue3
dc.description.page195-212
dc.description.codenIJCVE
dc.identifier.isiut000082187500002
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