Rectifying homographies for stereo vision: analytical solution for minimal distortion

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dc.contributor.authorLafiosca, Pasquale
dc.contributor.authorCeccaroni, Marta
dc.date.accessioned2022-08-03T15:13:53Z
dc.date.available2022-08-03T15:13:53Z
dc.date.issued2022-07-07
dc.description.abstractStereo rectification is the determination of two image transformations (or homographies) that map corresponding points on the two images, projections of the same point in the 3D space, onto the same horizontal line in the transformed images. Rectification is used to simplify the subsequent stereo correspondence problem and speeding up the matching process. Rectifying transformations, in general, introduce perspective distortion on the obtained images, which shall be minimised to improve the accuracy of the following algorithm dealing with the stereo correspondence problem. The search for the optimal transformations is usually carried out relying on numerical optimisation. This work proposes a closed-form solution for the rectifying homographies that minimise perspective distortion. The experimental comparison confirms its capability to solve the convergence issues of the previous formulation. Its Python implementation is provided.en_UK
dc.identifier.citationLafiosca P, Ceccaroni M. (2022) Rectifying homographies for stereo vision: analytical solution for minimal distortion. In: SAI 2022: Intelligent Computing, 14-15 July 2022, London, UKen_UK
dc.identifier.issn2367-3370
dc.identifier.urihttps://doi.org/10.1007/978-3-031-10464-0_33
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/18279
dc.language.isoenen_UK
dc.publisherSpringeren_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectStereo visionen_UK
dc.subjectStereo image processingen_UK
dc.subjectImage rectificationen_UK
dc.subjectEpipolar geometryen_UK
dc.titleRectifying homographies for stereo vision: analytical solution for minimal distortionen_UK
dc.typeBook chapteren_UK

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