Salient Point and Scale Detection by Minimum Likelihood
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Salient Point and Scale Detection by Minimum Likelihood. / Pedersen, Kim Steenstrup; Loog, Marco; van Dorst, Pieter.
Gaussian processes in practice. Microtome Publishing, 2007. p. 59-72 (JMLR: Workshop and Conference Proceedings; No. 1).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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TY - GEN
T1 - Salient Point and Scale Detection by Minimum Likelihood
AU - Pedersen, Kim Steenstrup
AU - Loog, Marco
AU - van Dorst, Pieter
PY - 2007
Y1 - 2007
N2 - We propose a novel approach for detection of salient image pointsand estimation of their intrinsic scales based on the fractionalBrownian image model. Under this model images are realisations of aGaussian random process on the plane. We define salient points aspoints that have a locally unique image structure. Such points areusually sparsely distributed in images and carry importantinformation about the image content. Locality is defined in terms ofthe measurement scale of the filters used to describe the imagestructure. Here we use partial derivatives of the image functiondefined using linear scale space theory. We propose to detectsalient points and their intrinsic scale by detecting points inscale-space that locally minimise the likelihood under the model.
AB - We propose a novel approach for detection of salient image pointsand estimation of their intrinsic scales based on the fractionalBrownian image model. Under this model images are realisations of aGaussian random process on the plane. We define salient points aspoints that have a locally unique image structure. Such points areusually sparsely distributed in images and carry importantinformation about the image content. Locality is defined in terms ofthe measurement scale of the filters used to describe the imagestructure. Here we use partial derivatives of the image functiondefined using linear scale space theory. We propose to detectsalient points and their intrinsic scale by detecting points inscale-space that locally minimise the likelihood under the model.
M3 - Article in proceedings
T3 - JMLR: Workshop and Conference Proceedings
SP - 59
EP - 72
BT - Gaussian processes in practice
PB - Microtome Publishing
Y2 - 12 June 2006 through 13 June 2006
ER -
ID: 2030833