Learning an object model for feature matching in clutter

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

Volumn 2749, Issue , 2003, Pages 193-199

  Tamminen, Toni ^a   Lampinen, Jouko ^a  

^a AALTO UNIVERSITY   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

CLUTTER (INFORMATION THEORY); GABOR FILTERS; VECTOR SPACES;

FEATURE MATCHING; FILTER RESPONSE; MATCHING MODELS; MATCHING PERFORMANCE; MATCHING SYSTEM; OBJECT SHAPE; PRIOR MODELING; SHAPE VARIATIONS;

PROBABILITY DISTRIBUTIONS;

EID: 35248818883     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45103-x_27     Document Type: Article

References (11)

1. Cox, G.S.: Template matching and measures of match in image processing. Department of Computer Science, University of Cape Town (1995)
2. Xu, G., Zhang, Z.: Epipolar Geometry in Stereo, Motion and Object Recognition: A Unified Approach. Computational Imaging and Vision, Vol. 6. Kluwer Academic Publishers (1996)
3. Zhang, Z.: Token tracking in a cluttered scene. Technical report RR-2072, Institut National de Recherce en Informatique et en Automatique (1994)
4. Wiskott, L., Fellous, J.-M., Krüger, N., von der Malsburg, C.: Face Recognition by Elastic Bunch Graph Matching. In Jain, L.C., Halici, U., Hayashi, I., and Lee, S.B. (eds.), Intelligent Biometric Techniques in Fingerprint and Face Recognition. CRC Press (1999)
5. Gelman, A., Carlin, J.B., Stern, H.S., Rubin, D.R.: Bayesian Data Analysis. Texts in Statistical Science. Chapman & Hall (1995)
6. Daugman, J.G.: Complete discrete 2-D Gabor transforms by neural networks for image analysis and compression. IEEE Trans, on Acoustics, Speech, and Signal Processing 36 (1988) 1169-1179
7. Hassani, S.: Mathematical Physics. A Modern Introduction to its Foundations. Springer (1998)
8. Tamminen, T., Lampinen, J.: Bayesian Object Matching with Hierarchical Priors and Markov Chain Monte Carlo. In Bernardo, J.M., Dawid, A.P., Berger, J.O., West, M. (eds.), Bayesian Statistics 7. In press. Oxford University Press (2003)
9. Gilks, W.R., Richardson, S., Spiegelhalter, D.J. (eds.): Markov Chain Monte Carlo in Practice. Chapman & Hall (1996)
10. Cootes, T.F., Edwards, G.J., Taylor, C.J.: Active Appearance Models. IEEE Trans, on Pattern Analysis and Machine Intelligence 23 (2001) 681-685.
11. Stegmann, M.B.: Analysis and Segmentation of Face Images using Point Annotations and Linear Subspace Techniques. Technical Report, Informatics and Mathematical Modelling, Technical University of Denmark (2002)