A unified formulation of invariant point pattern matching

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dc.contributor.authorCaetano, Tiberio
dc.contributor.authorCaelli, Terry
dc.coverage.spatialHong Kong
dc.date.accessioned2015-12-08T22:24:42Z
dc.date.createdAugust 20-24 2006
dc.date.issued2006
dc.date.updated2015-12-08T08:58:50Z
dc.description.abstractWe present a unified framework for modeling and solving invariant point pattern matching problems. Invariant features are encoded as potentials in a probabilistic graphical model. By using a specific kind of graph topology, different types of invariant matching models can be implemented via tree-width selection. Models with tree-widths 1, 2, 3 and 4 implement translation, similarity, affine and protective invariant point matching, respectively. The optimal match is then found by exploiting the Markov structure of the graph through the generalized distributive law in a dynamic programming setting. In the absence of noise in the point coordinates, the solutions found are optimal. Our early experiments suggest the approach is robust to outliers and moderate noise.
dc.identifier.isbn0769525210
dc.identifier.urihttp://hdl.handle.net/1885/33122
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE Inc)
dc.relation.ispartofseriesInternational Conference on Pattern Recognition (ICPR 2006)
dc.sourceProceedings of the 18th International Conference on Pattern Recognition
dc.source.urihttp://ieeexplore.ieee.org/iel5/11159/35817/01698811.pdf?isnumber=35817&prod=CNF&http://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=35817&isYear=2006
dc.subjectKeywords: Graph theory; Markov processes; Mathematical models; Probability; Problem solving; Invariant point pattern matching; Markov structures; Probabilistic graphical models; Protective invariant point matching; Pattern matching
dc.titleA unified formulation of invariant point pattern matching
dc.typeConference paper
local.bibliographicCitation.lastpage124
local.bibliographicCitation.startpage121
local.contributor.affiliationCaetano, Tiberio, College of Engineering and Computer Science, ANU
local.contributor.affiliationCaelli, Terry, College of Engineering and Computer Science, ANU
local.contributor.authoremailu4590840@anu.edu.au
local.contributor.authoruidCaetano, Tiberio, u4590840
local.contributor.authoruidCaelli, Terry, u971266
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor080104 - Computer Vision
local.identifier.ariespublicationu3357961xPUB99
local.identifier.doi10.1109/ICPR.2006.192
local.identifier.scopusID2-s2.0-34147182233
local.identifier.uidSubmittedByu3357961
local.type.statusPublished Version

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