The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
A multiple-baseline stereo
Abstract
A stereo matching method that uses multiple stereo pairs with various baselines generated by a lateral displacement of a camera to obtain precise distance estimates without suffering from ambiguity is presented. Matching is performed simply by computing the sum of squared-difference (SSD) values. The SSD functions for individual stereo pairs are represented with respect to the inverse distance and are then added to produce the sum of SSDs. This resulting function is called the SSSD-in-inverse-distance. It is shown that the SSSD-in-inverse-distance function exhibits a unique and clear minimum at the correct matching position, even when the underlying intensity patterns of the scene include ambiguities or repetitive patterns. The authors first define a stereo algorithm based on the SSSD-in-inverse-distance and present a mathematical analysis to show how the algorithm can remove ambiguity and increase precision. Experimental results with real stereo images are presented to demonstrate the effectiveness of the algorithm.>
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Cites
A computational theory of human stereo vision
Marr, D., & Poggio, T. (1979) · Proceedings of the Royal Society of London. Series B. Biological Sciences · doi:10.1098/rspb.1979.0029 · Cited by 1,801
Epipolar-plane image analysis: An approach to determining structure from motion
Bolles, R. C., Baker, H. H., & Marimont, D. H. (1987) · International Journal of Computer Vision · doi:10.1007/bf00128525 · Cited by 892
Kalman filter-based algorithms for estimating depth from image sequences
Matthies, L., Kanade, T., & Szeliski, R. (1989) · International Journal of Computer Vision · doi:10.1007/bf00133032 · Cited by 716
Self-citationComputational Experiments with a Feature Based Stereo Algorithm
Grimson, W. E. L. (1985) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1985.4767615 · Cited by 529
A Theory of Human Stereo Vision
Marr, D., & Poggio, T. (1977) · Defense Technical Information Center (DTIC) · Cited by 309
VISUAL MAPPING BY A ROBOT ROVER
Moravec, H. (1979) · International Joint Conference on Artificial Intelligence · Cited by 290
Stochastic stereo matching over scale
Barnard, S. T. (1989) · International Journal of Computer Vision · doi:10.1007/bf00054836 · Cited by 242
A locally adaptive window for signal matching
Okutomi, M., & Takeo Kanade, A. (1992) · International Journal of Computer Vision · doi:10.1007/bf00128133 · Cited by 155
Self-citation
Cited by
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
Scharstein, D., & Szeliski, R. (2002) · International Journal of Computer Vision · doi:10.1023/a:1014573219977 · Cited by 6,740
Bundle Adjustment — A Modern Synthesis
Triggs, B., McLauchlan, P. F., Hartley, R. I., & Fitzgibbon, A. W. (2000) · Lecture Notes in Computer Science · doi:10.1007/3-540-44480-7_21 · Cited by 3,988
A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms
Seitz, S. M., Curless, B., Diebel, J., Scharstein, D., & Szeliski, R. (2006) · 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (CVPR'06) · doi:10.1109/cvpr.2006.19 · Cited by 2,457
A Theory of Shape by Space Carving
Kutulakos, K. N., & Seitz, S. M. (2000) · International Journal of Computer Vision · doi:10.1023/a:1008191222954 · Cited by 1,254
A taxonomy and evaluation of dense two-frame stereo correspondence algorithms
Scharstein, D., Szeliski, R., & Zabih, R. (2002) · Proceedings IEEE Workshop on Stereo and Multi-Baseline Vision (SMBV 2001) · doi:10.1109/smbv.2001.988771 · Cited by 1,084
Metadata
- Authors
- Okutomi, M., & Kanade, T.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 1993-04
- Volume
- 15
- Issue
- 4
- Pages
- 353-363
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2561377267
- Cited by
- 939
- References
- 8
- FWCI
- 24.41
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
