



@conference {2446,
	title = {Spectral methods in image segmentation: A combined approach},
	booktitle = {Lecture Notes in Computer ScienceLect. Notes Comput. Sci.},
	series = {Second Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2005},
	volume = {3523},
	year = {2005},
	note = {Conference code: 65649Cited By (since 1996): 1Export Date: 21 November 2012Source: ScopusLanguage of Original Document: EnglishCorrespondence Address: Monteiro, F.C.; INEB - Instituto de Engenharia Biom{\'e}dica, Campus de Santa Apol{\'o}nia, Apartado 134, 5301-857 Bragan{\c c}a, Portugal; email: monteiro@ipb.ptReferences: Fowlkes, C., Belongie, S., Chung, F., Malik, J., Spectral grouping using nystr{\"o}m method (2004) Trans. on Pattern Analysis and Machine Intelligence, 26 (2), pp. 214-225;Malik, J., Belongie, S., Leung, T., Shi, T., Contour and texture analysis for image segmentation (2001) International Journal of Computer Vision, 43 (1), pp. 7-27; 
Martin, D., Fowlkes, C., Tal, D., Malik, J., A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics (2001) IEEE Int. Conf. on Computer Vision, 2, pp. 416-424; 
Meila, M., Shi, J., Learning segmentation by random walks (2000) Neural Information Processing Systems, pp. 873-879; 
Ng, A., Jordan, M., Weiss, Y., On spectral clustering: Analysis and an algorithm (2002) Advances in Neural Information Processing Systems, 14, pp. 849-856; 
Scott, D.S., Solving sparse symmetric generalized eigenvalue without factorization (1981) SIAM Journal of Numerical Analisys, 18, pp. 102-110. , http://www.netlib.org/laso/snlaso.f; 
Scott, G.L., Longuet-Higgins, H.C., Feature grouping by "relocalisation" of eigenvectors of the proximity matrix (1990) Proc. British Machine Vision Conf., pp. 103-108; 
Shi, J., Malik, J., Normalized cuts and image segmentation (2000) IEEE Trans. on Pattern Analysis and Machine Intelligence, 22 (8), pp. 888-905; 
Weiss, Y., Segmentation using eigenvectors: A unifying view (1999) International Conference on Computer Vision, pp. 975-982; 
Wertheimer, M., Laws of organization in perceptual forms (1938) A Sourcebook of Gestalt Psychology, pp. 71-88. , W. B. Ellis Editor; 
Wu, Z., Leahy, R., An optimal graph theoretic approach to data clustering: Theory and its application to image segmentation (1993) IEEE Trans. on Pattern Analysis and Machine Intelligence, 15, pp. 1101-1113; 
Yu, S., Shi, J., Multiclass spectral clustering (2003) International Conference on Computer Vision, pp. 313-319. , Nice, France
},
	month = {2005///},
	pages = {191 - 198},
	address = {Estoril},
	abstract = {Grouping and segmentation of images remains a challenging problem in computer vision. Recently, a number of authors have demonstrated a good performance on this task using spectral methods that are based on the eigensolution of a similarity matrix. In this paper, we implement a variation of the existing methods that combines aspects from several of the best-known eigenvector segmentation algorithms to produce a discrete optimal solution of the relaxed continuous eigensolution. {\textcopyright} Springer-Verlag Berlin Heidelberg 2005.},
	keywords = {Algorithms, Computer vision, Discrete optimal solution, Eigensolution, Eigenvalues and eigenfunctions, Image segmentation, Matrix algebra, Problem solving, Similarity matrix, Spectral methods},
	isbn = {03029743 (ISSN)},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-25144437374\&partnerID=40\&md5=5b6351af4ac58a16c41b5558a48ae9e2},
	author = {Monteiro, F.C. and Campilho, A.C.},
	editor = {Marques J.S. and Perez de la Blanca N. and Pina P.}
}
