The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Parallel and deterministic algorithms from MRFs: surface reconstruction
Abstract
Deterministic approximations to Markov random field (MRF) models are derived. One of the models is shown to give in a natural way the graduated nonconvexity (GNC) algorithm proposed by A. Blake and A. Zisserman (1987). This model can be applied to smooth a field preserving its discontinuities. A class of more complex models is then proposed in order to deal with a variety of vision problems. All the theoretical results are obtained in the framework of statistical mechanics and mean field techniques. A parallel, iterative algorithm to solve the deterministic equations of the two models is presented, together with some experiments on synthetic and real images.>
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Cites
Optimization by Simulated Annealing
Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983) · Science · doi:10.1126/science.220.4598.671 · Cited by 45,134
Equation of State Calculations by Fast Computing Machines
Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., & Teller, E. (1953) · The Journal of Chemical Physics · doi:10.1063/1.1699114 · Cited by 37,192
Stochastic relaxation, gibbs distributions, and the bayesian restoration of images.
Geman, S., & Geman, D. (1984) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1984.4767596 · Cited by 17,949
Solutions of Ill-Posed Problems.
Bell, J. B., Tikhonov, A. N., & Arsenin, V. Y. (1978) · Mathematics of Computation · doi:10.2307/2006360 · Cited by 8,101
Blake, A., & Zisserman, A. (1987) · The MIT Press eBooks · doi:10.7551/mitpress/7132.001.0001 · Cited by 2,105
Finding Edges and Lines in Images
Canny, J. (1983) · DSpace@MIT (Massachusetts Institute of Technology) · Cited by 833
Practical Approximate Solutions to Linear Operator Equations When the Data are Noisy
Wahba, G. (1977) · SIAM Journal on Numerical Analysis · doi:10.1137/0714044 · Cited by 798
Probabilistic Solution of Ill-Posed Problems in Computational Vision
Marroquin, J., Mitter, S., & Poggio, T. (1987) · Journal of the American Statistical Association · doi:10.1080/01621459.1987.10478393 · Cited by 766
Ill-posed problems in early vision
Bertero, M., Poggio, T. A., & Torre, V. (1988) · Proceedings of the IEEE · doi:10.1109/5.5962 · Cited by 723
Analog "neuronal" networks in early vision.
Koch, C., Marroquin, J., & Yuille, A. (1986) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.83.12.4263 · Cited by 278
Cited by
Chen, L.-C., Papandreou, G., Kokkinos, I., Murphy, K., & Yuille, A. L. (2018) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2017.2699184 · Cited by 22,392
Chen, L.-C., Papandreou, G., Kokkinos, I., Murphy, K., & Yuille, A. L. (2016) · arXiv · doi:10.48550/arxiv.1606.00915 · Cited by 22,392
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
Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs
Chen, L.-C., Papandreou, G., Kokkinos, I., Murphy, K., & Yuille, A. L. (2014) · arXiv · doi:10.48550/arxiv.1412.7062 · Cited by 4,213
Warfield, S. K., Zou, K. H., & Wells, W. M. (2004) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2004.828354 · Cited by 2,072
Metadata
- Authors
- Geiger, D., & Girosi, F.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 1991-05
- Volume
- 13
- Issue
- 5
- Pages
- 401-412
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2020278873
- Cited by
- 447
- References
- 14
- FWCI
- 32.21
- Type
- journal article
- Language
- en
- Open access
- closed
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- Geiger, D., & Girosi, F. (1991). Parallel and deterministic algorithms from MRFs: surface reconstruction. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/34.134040
Data sources
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.