Spectral Grouping Using the Nyström Method

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Spectral Grouping Using the Nyström Method. / Fowlkes, Charless; Belongie, Serge; Chung, Fan; Malik, Jitendra.

In: IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 26, No. 2, 02.2004, p. 214-225.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Fowlkes, C, Belongie, S, Chung, F & Malik, J 2004, 'Spectral Grouping Using the Nyström Method', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 2, pp. 214-225. https://doi.org/10.1109/TPAMI.2004.1262185

APA

Fowlkes, C., Belongie, S., Chung, F., & Malik, J. (2004). Spectral Grouping Using the Nyström Method. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(2), 214-225. https://doi.org/10.1109/TPAMI.2004.1262185

Vancouver

Fowlkes C, Belongie S, Chung F, Malik J. Spectral Grouping Using the Nyström Method. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2004 Feb;26(2):214-225. https://doi.org/10.1109/TPAMI.2004.1262185

Author

Fowlkes, Charless ; Belongie, Serge ; Chung, Fan ; Malik, Jitendra. / Spectral Grouping Using the Nyström Method. In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 2004 ; Vol. 26, No. 2. pp. 214-225.

Bibtex

@article{143adefeea3b4f2a9a29c7224fe6c89e,
title = "Spectral Grouping Using the Nystr{\"o}m Method",
abstract = "Spectral graph theoretic methods have recently shown great promise for the problem of image segmentation. However, due to the computational demands of these approaches, applications to large problems such as spatiotemporal data and high resolution imagery have been slow to appear. The contribution of this paper is a method that substantially reduces the computational requirements of grouping algorithms based on spectral partitioning making it feasible to apply them to very large grouping problems. Our approach is based on a technique for the numerical solution of eigenfunction problems known as the Nystr{\"o}m method. This method allows one to extrapolate the complete grouping solution using only a small number of samples. In doing so, we leverage the fact that there are far fewer coherent groups in a scene than pixels.",
keywords = "Clustering, Image and video segmentation, Normalized cuts, Nystr{\"o}m approximation, Spectral graph theory",
author = "Charless Fowlkes and Serge Belongie and Fan Chung and Jitendra Malik",
year = "2004",
month = feb,
doi = "10.1109/TPAMI.2004.1262185",
language = "English",
volume = "26",
pages = "214--225",
journal = "IEEE Transactions on Pattern Analysis and Machine Intelligence",
issn = "0162-8828",
publisher = "Institute of Electrical and Electronics Engineers",
number = "2",

}

RIS

TY - JOUR

T1 - Spectral Grouping Using the Nyström Method

AU - Fowlkes, Charless

AU - Belongie, Serge

AU - Chung, Fan

AU - Malik, Jitendra

PY - 2004/2

Y1 - 2004/2

N2 - Spectral graph theoretic methods have recently shown great promise for the problem of image segmentation. However, due to the computational demands of these approaches, applications to large problems such as spatiotemporal data and high resolution imagery have been slow to appear. The contribution of this paper is a method that substantially reduces the computational requirements of grouping algorithms based on spectral partitioning making it feasible to apply them to very large grouping problems. Our approach is based on a technique for the numerical solution of eigenfunction problems known as the Nyström method. This method allows one to extrapolate the complete grouping solution using only a small number of samples. In doing so, we leverage the fact that there are far fewer coherent groups in a scene than pixels.

AB - Spectral graph theoretic methods have recently shown great promise for the problem of image segmentation. However, due to the computational demands of these approaches, applications to large problems such as spatiotemporal data and high resolution imagery have been slow to appear. The contribution of this paper is a method that substantially reduces the computational requirements of grouping algorithms based on spectral partitioning making it feasible to apply them to very large grouping problems. Our approach is based on a technique for the numerical solution of eigenfunction problems known as the Nyström method. This method allows one to extrapolate the complete grouping solution using only a small number of samples. In doing so, we leverage the fact that there are far fewer coherent groups in a scene than pixels.

KW - Clustering

KW - Image and video segmentation

KW - Normalized cuts

KW - Nyström approximation

KW - Spectral graph theory

UR - http://www.scopus.com/inward/record.url?scp=0742286179&partnerID=8YFLogxK

U2 - 10.1109/TPAMI.2004.1262185

DO - 10.1109/TPAMI.2004.1262185

M3 - Journal article

C2 - 15376896

AN - SCOPUS:0742286179

VL - 26

SP - 214

EP - 225

JO - IEEE Transactions on Pattern Analysis and Machine Intelligence

JF - IEEE Transactions on Pattern Analysis and Machine Intelligence

SN - 0162-8828

IS - 2

ER -

ID: 302055737