Robust fitting by adaptive-scale residual consensus

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

Volumn 3023, Issue , 2004, Pages 107-118

  Wang, Hanzi ^a   Suter, David ^a  

^a MONASH UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ESTIMATION; IMAGE SEGMENTATION; STATISTICS;

ADAPTIVE SCALE; CORRUPTED DATA; FUNDAMENTAL MATRIX; MODEL-BASED OPC; RANGE IMAGE SEGMENTATION; RESIDUAL CONSENSUS; ROBUST FITTINGS; ROBUST METHODS;

COMPUTER VISION;

EID: 35048878420     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-24672-5_9     Document Type: Article

References (25)

1. Bab-Hadiashar, A., Suter, D.: Robust Optic Flow Computation. International Journal of Computer Vision. 29(1) (1998) 59-77
2. Chen, H., Meer, P.: Robust Regression with Projection Based M-estimators. in ICCV. Nice, France (2003) 878-885
3. Comaniciu, D., Meer, P.: Mean Shift Analysis and Applications, in ICCV, Kerkyra, Greece. (1999) 1197-1203
4. Comaniciu, D., Ramesh, V., Bue, A.D.: Multivariate Saddle Point Detection for Statistical Clustering, in ECCV. Copenhagen, Danmark (2002) 561-576
5. Fischler, M.A., Rolles, R.C.: Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. Commun. ACM. 24(6) (1981) 381-395
6. Haralick, R.M.: Computer vision theory: The lack thereof. CVGIP. 36 (1986) 372-386
7. Hoover, A., Jean-Baptiste, G., Jiang., X.: An Experimental Comparison of Range Image Segmentation Algorithms. IEEE Trans. PAMI. 18(7) (1996) 673-689
8. Hough, P.V.C.: Methods and means for recognising complex patterns. U.S. Patent 3 069 654. (1962)
9. Huber, P.J.: Robust Statistics. New York, Wiley. (1981)
10. Lee, K.-M., Meer, P., Park, R.-H.: Robust Adaptive Segmentation of Range Images. IEEE Trans. PAMI. 20(2) (1998) 200-205
11. Miller, J.V., Stewart, C.V.: MUSE: Robust Surface Fitting Using Unbiased Scale Estimates, in CVPR, San Francisco (1996) 300-306
12. Rousseeuw, P.J., Croux, C.: Alternatives to the Median Absolute Derivation. Journal of the American Statistical Association. 88(424) (1993) 1273-1283
13. Rousseeuw, P.J., Leroy, A.: Robust Regression and outlier detection. John Wiley & Sons, New York. (1987)
14. Silverman, B.W.: Density Estimation for Statistics and Data Analysis London: Chapman and Hall. (1986).
15. Stewart, C.V.: MINPRAN: A New Robust Estimator for Computer Vision. IEEE Trans. PAMI. 17(10) (1995) 925-938
16. Stewart, C.V.: Bias in Robust Estimation Caused by Discontinuities and Multiple Structures. IEEE Trans. PAMI. 19(8) (1997) 818-833
17. Torr, P., D. Murray: The Development and Comparison of Robust Methods for Estimating the Fundamental Matrix. International Journal of Computer Vision. 24 (1997) 271-300
18. Torr, P., Zisserman, A.: MLESAC: A New Robust Estimator With Application to Estimating Image Geometry. Computer Vision and Image Understanding. 78(1) (2000) 138-156
19. Wand, M.P., Jones, M.: Kernel Smoothing. Chapman & Hall. (1995)
20. Wang, H., Suter, D.: False-Peaks-Avoiding Mean Shift Method for Unsupervised Peak-Valley Sliding Image Segmentation, in Digital Image Computing Techniques and Applications. Sydney, Australia (2003) 581-590
21. Wang, H., Suter, D.: MDPE: A Very Robust Estimator for Model Fitting and Range Image Segmentation. International Journal of Computer Vision. (2003) to appear
22. Wang, H., Suter, D.: Variable bandwidth QMDPE and its application in robust optic flow estimation, in ICCV. Nice, France (2003) 178-183
23. Wang, H., Suter, D.: Robust Adaptive-Scale Parametric Model Estimation for Computer Vision, submitted to IEEE Trans. PAMI. (2003)
24. Yu, X., Bui, T.D., Krzyzak, A.: Robust Estimation for Range Image Segmentation and Reconstruction. IEEE Trans PAMI. 16(5) (1994) 530-538
25. Zhang, Z., et al.: A Robust Technique for Matching Two Uncalibrated Image Through the Recovery of the Unknown Epipolar Geometry. Artificial Intelligence. 78 (1995) 87-11