Salient Point and Scale Detection by Minimum Likelihood

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

Standard

Salient Point and Scale Detection by Minimum Likelihood. / Pedersen, Kim Steenstrup; Loog, Marco; van Dorst, Pieter.

Gaussian processes in practice. Microtome Publishing, 2007. s. 59-72 (JMLR: Workshop and Conference Proceedings; Nr. 1).

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

Harvard

Pedersen, KS, Loog, M & van Dorst, P 2007, Salient Point and Scale Detection by Minimum Likelihood. i Gaussian processes in practice. Microtome Publishing, JMLR: Workshop and Conference Proceedings, nr. 1, s. 59-72, Gaussian Processes in Practice Workshop, Bletchley Park, Storbritannien, 12/06/2006. <http://jmlr.csail.mit.edu/proceedings/papers/v1/>

APA

Pedersen, K. S., Loog, M., & van Dorst, P. (2007). Salient Point and Scale Detection by Minimum Likelihood. I Gaussian processes in practice (s. 59-72). Microtome Publishing. JMLR: Workshop and Conference Proceedings Nr. 1 http://jmlr.csail.mit.edu/proceedings/papers/v1/

Vancouver

Pedersen KS, Loog M, van Dorst P. Salient Point and Scale Detection by Minimum Likelihood. I Gaussian processes in practice. Microtome Publishing. 2007. s. 59-72. (JMLR: Workshop and Conference Proceedings; Nr. 1).

Author

Pedersen, Kim Steenstrup ; Loog, Marco ; van Dorst, Pieter. / Salient Point and Scale Detection by Minimum Likelihood. Gaussian processes in practice. Microtome Publishing, 2007. s. 59-72 (JMLR: Workshop and Conference Proceedings; Nr. 1).

Bibtex

@inproceedings{0a2f4240b55111dcbee902004c4f4f50,
title = "Salient Point and Scale Detection by Minimum Likelihood",
abstract = "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.",
author = "Pedersen, {Kim Steenstrup} and Marco Loog and {van Dorst}, Pieter",
year = "2007",
language = "English",
series = "JMLR: Workshop and Conference Proceedings",
publisher = "Microtome Publishing",
number = "1",
pages = "59--72",
booktitle = "Gaussian processes in practice",
note = "null ; Conference date: 12-06-2006 Through 13-06-2006",

}

RIS

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