Simultaneous segmentation of range and color images based on Bayesian decision theory

Proceedings - 1st Canadian Conference on Computer and Robot Vision

Volumn , Issue , 2004, Pages 58-63

  Boulanger, Pierre ^a  

^a UNIVERSITY OF ALBERTA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN DECISION THEORY; COLOR SIGNALS; MAXIMUM LIKELIHOOD (ML); STATISTICAL DISTRIBUTIONS;

ALGORITHMS; COLOR; COMPUTATIONAL COMPLEXITY; DECISION THEORY; IMAGE SENSORS; MATHEMATICAL MODELS; MATRIX ALGEBRA; PAINTING; PROBABILITY; SENSITIVITY ANALYSIS; SIGNAL PROCESSING;

IMAGE SEGMENTATION;

EID: 4544248934     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CCCRV.2004.1301422     Document Type: Conference Paper

References (15)

1. P. Allen, I. Stamos, A. Gueorguiev, E.Gold, and P. Blaer, AVENUE:Automated Site Modeling in Urban Environment,hird Conference on 3D Digital Imaging and Modeling, Qubec, Canada, May 28th-June 1st, 2001.
2. R. Baribeau, M. Rioux, and G. Godin,Color reflectance modeling using a polychromatic laser range sensor, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. PAMI-14, no. 2, pp. 263-269, 1992
3. P.J. Besl and R.C. Jain, Segmentation through variable-order surface fitting, IEEE Trans. on Pattern Analysis and Machine Intelligence,Vol. PAMI-10, no. 2, pp. 167-192, 1988.
4. P. Boulanger, F. Blais, and P. Cohen, Detection of depth and orientation discontinuities in range images using mathemat ical morphology, 10th International Conference on Pattern Recognition, Atlantic City, 1990.
5. R.O. Duda, D. Nitzan, and P. Barret, Use of range and reflectance data to find planer surface regions, IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. PAMI-1 no. 3, pp. 259-271, 1979.
6. B. Gil, A. Mitiche,and J.K. Aggarwal, J.K.,Experiments in combining intensity and range edge maps, Computer Vision, Graphics, and Image Processing,Vol. 21 no. 3, pp. 395-411, 1983.
7. J.K. Hackett and M. Shah, Segmentation using intensity and range data, Optical Engineering, Vol. 28, no. 6, pp. 667-674, 1989.
8. T. Koezuka, Y. Kakinoki, Y. Suto, M. Nakashima, and T. Inagaki,High-speed 3-D vision system using range and intensity images covering a wide area, Application of Artificial Intelligence VII, Vol. SPIE-1095, pp. 1134-1141, 1989.
9. R.C. Luo and M.G. Kay,Multisensor integration and fusion in intelligent systems, IEEE Trans. on System, Man, and Cybernetics, Vol. SMC-19. no. 6, pp. 901-931, 1989.
10. F. Prieto, T. Redarce, P. Boulanger, and R. Lepage R.,Tolerance Control with high quality 3D data, Third Conference on 3D Digital Imaging and Modeling, Qubec, Canada, May 28th-June 1st,2001.
11. M. Rioux M., F. Blais F., J.A. Beraldin and P. Boulanger, Range image sensors development at NRC laboratories, Proc. of the Workshop on Interpretation of 3D Scenes, Austin, TX, November 27-29, 1989.
12. P.J. Rousseeuw and A.M. Leroy,Robust regression and outlier detection, J. Wiley and Sons, 1987.
13. H. Rushmeier and F. Bernardini, Computing consistent normals and colors from photometric data,2nd International Conference on 3D Digital Imaging and Modeling (3DIM '99) October 4-8, 1999.
14. Y. Shirai, 3-D computer vision and applications, IEEE International Conf. on Pattern Recognition, pp. 236-245, 1992.
15. I. Stamos and P. Allen, Automatic registration of 2-D with 3-D imagery in urban environments, Technical report, Dept. of Computing Science, Columbia, University, 2000.