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Shape-Adapted Smoothing in Estimation of 3-D Depth Cues from Affine Distortions of Local 2-D Brightness Structure
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.ORCID iD: 0000-0002-9081-2170
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
1994 (English)In: Computer Vision — ECCV '94: Third European Conference on Computer Vision Stockholm, Sweden, May 2–6, 1994 Proceedings, Volume I, 1994, 389-400 p.Conference paper, Published paper (Refereed)
Abstract [en]

Rotationally symmetric operations in the image domain may give rise to shape distortions. This article describes a way of reducing this effect for a general class of methods for deriving 3-D shape cues from 2-D image data, which are based on the estimation of locally linearized distortion of brightness patterns. By extending the linear scale-space concept into an affine scale-spacerepresentation and performing affine shape adaption of the smoothing kernels, the accuracy of surface orientation estimates derived from texture and disparity cues can be improved by typically one order of magnitude. The reason for this is that the image descriptors, on which the methods are based, will be relative invariant under affine transformations, and the error will thus be confined to the higher-order terms in the locally linearized perspective mapping.

Place, publisher, year, edition, pages
1994. 389-400 p.
National Category
Computer Science Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:kth:diva-58576DOI: 10.1007/3-540-57956-7_42ISBN: 978-3-540-57956-4 (print)OAI: oai:DiVA.org:kth-58576DiVA: diva2:473373
Conference
3rd European Conf. on Computer Vision (Stockholm, Sweden)
Note

QC 20130423

Available from: 2012-01-05 Created: 2012-01-05 Last updated: 2013-04-23Bibliographically approved

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fulltext(198 kB)329 downloads
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Lindeberg, Tony

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CiteExportLink to record
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Language
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