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Energy functions for regularization algorithmsRegularization techniques are widely used for inverse problem solving in computer vision such as surface reconstruction, edge detection, or optical flow estimation. Energy functions used for regularization algorithms measure how smooth a curve or surface is, and to render acceptable solutions these energies must verify certain properties such as invariance with Euclidean transformations or invariance with parameterization. The notion of smoothness energy is extended here to the notion of a differential stabilizer, and it is shown that to void the systematic underestimation of undercurvature for planar curve fitting, it is necessary that circles be the curves of maximum smoothness. A set of stabilizers is proposed that meet this condition as well as invariance with rotation and parameterization.
Document ID
19930059856
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Delingette, H.
(NASA Headquarters Washington, DC United States)
Hebert, M.
(NASA Headquarters Washington, DC United States)
Ikeuchi, K.
(Carnegie Mellon Univ. Pittsburgh, PA, United States)
Date Acquired
August 16, 2013
Publication Date
January 1, 1991
Publication Information
Publication: In: Geometric methods in computer vision; Proceedings of the Meeting, San Diego, CA, July 25, 26, 1991 (A93-43851 17-67)
Publisher: Society of Photo-Optical Instrumentation Engineers
Subject Category
Numerical Analysis
Accession Number
93A43853
Funding Number(s)
CONTRACT_GRANT: ARPA ORDER 4976
CONTRACT_GRANT: NAGW-1175
Distribution Limits
Public
Copyright
Other

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