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Stereo error detection, correction, and evaluation
February 1989 (vol. 11 no. 2)
pp. 113,114,115,116,117,118,119,120
An algorithm is presented for error detection and correction of disparity, as a process separate from stereo matching, with the contention that matching is not necessarily the best way to utilize all the physical constraints characteristic to stereopsis. As a result of the bias in stereo research towards matching, vision tasks like surface interpolation and object modeling have to accept erroneous data from the stereo matchers without the benefits of any intervening stage of error correction. An algorithm which identifies all errors in disparity data that can be detected on the basis of figural continuity and corrects them is presented. The algorithm can be used as a postprocessor to any edged-based stereo matching algorithm, and can additionally be used to automatically provide quantitative evaluations on the performance of matching algorithms of this class.<>

[1] S. T. Barnard and M. A. Fischler, "Computational stereo,"Comput. Surveys, vol. 14, no. 4, pp. 553-572, 1982.
[2] D. Marr,Vision. San Francisco, CA: Freeman, 1982.
[3] W. E. L. Grimson,From Images to Surfaces. Cambridge, MA: M.I.T. Press, 1981.
[4] G. Medioni and R. Nevatia, "Segment-based stereo matching,"Comput. Vision. Graphics, Image Processing, vol. 31, pp. 2-18, 1985.
[5] W. E. L. Grimson, "Computational experiments with a feature based stereo algorithm,"IEEE Trans. Pattern Anal. Machine Intell., vol. 7, no. 1, 1985.
[6] J. E. W. Mayhew and J. P. Frisby, "The computation of binocular edges,"Perception, vol. 9, pp. 69-86, 1980.
[7] J. E. W. Mayhew and J. P. Frisby, "Psychophysical and computational studies towards a theory of human stereopsis,"Artificial Intell., vol. 17, 1981.
[8] R. D. Arnold, "Automated stereo perception," Ph.D. thesis, Stanford Univ., Stanford, CA, Mar. 1983; Tech. Rep. AIM-351 and STAN-CS- 83-961.
[9] H. Baker, "Depth from edge and intensity based stereo," Dep. Comput. Sci., Stanford Univ., Stanford, CA, Tech. Rep. STAN-CS-82- 930, Sept. 1982.
[10] R. L. Henderson, W. J. Miller, and C. B. Grosch, "Automatic stereo recognition of man-made targets,"Soc. Photo-Opt. Instrum. Eng., vol. 186 (Digital Processing of Images), Aug. 1979.
[11] Y. Ohta and T. Kanade, "Stereo by intra and inter-scanline search using dynamic programming,"IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-5, 1983.
[12] R. Nevatia and K. R. Babu, "Linear feature extraction and description,"Comput. Graphics Image Processing, vol. 13, pp. 257-269, 1980.
[13] R. S. Wallace, "A modified Hough transform for lines," inProc. IEEE Comput. Soc. Conf. Computer Vision and Pattern Recognition, San Francisco, CA, June 1985.
[14] Y. Le Guilloux, "Determination automatique du mouvement dans une sequence d'images. Interet pour l'interpretation," Ph.D. dissertation, Ecole Nationale Supérieurre des Télécommunications, June 1984.
[15] M. J. Hannah, "Detection of errors in match disparities," inProc. Image Understanding Workshop, Sept. 1982.

Index Terms:
computerised pattern recognition,computer vision,error correction,computer vision,computerised pattern recognition,error detection,stereo matching,vision tasks,surface interpolation,Error correction,Layout,Stereo vision,Intelligent robots,Interpolation,Eyes,Humans,Information resources,Computerized monitoring
Citation:
"Stereo error detection, correction, and evaluation," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 11, no. 2, pp. 113,114,115,116,117,118,119,120, Feb. 1989, doi:10.1109/34.16708
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