Image modeling and segmentation using incremental bayesian mixture models

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4673 LNCS, Issue , 2007, Pages 596-603

  Constantinopoulos, Constantinos ^a   Likas, Aristidis ^a  

^a UNIVERSITY OF IOANNINA   (Greece)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORKS; COMPUTER SIMULATION; FEATURE EXTRACTION; IMAGE ANALYSIS; MATHEMATICAL MODELS; VARIATIONAL TECHNIQUES;

GAUSSIAN MIXTURE MODELS (GMM); IMAGE MODELING;

IMAGE SEGMENTATION;

EID: 38149029135     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-74272-2_74     Document Type: Conference Paper

References (5)

1. Carson, C., Belongie, S., Greenspan, H., Malik, J.: Blobworld: Image segmentation using expectation-maximization and its application to image querying. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(8), 1026-1038 (2002)
2. Li, S.Z.: Markov Random Field Modelling in Computer Vision. Springer, Heidelberg (2001)
3. Constantinopoulos, C., Likas, A.: Bayesian gaussian mixture learning based on variational component splitting. IEEE Transactions on Neural Networks 18(3), 745-755 (2007)
4. Corduneanu, A., Bishop, C.M.: Variational Bayesian model selection for mixture distributions. In: Artificial Intelligence and Statistics 2001, pp. 27-34. Morgan Kaufmann, San Francisco (2001)
5. 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. In: Proc. 8th Int'l Conf. Computer Vision, vol. 2, pp. 416-423 (2001)