The DOI matches its Crossref record; 63 of the 70 references it cites were found in a registry or an index.
A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms
Abstract
This paper presents a quantitative comparison of several multi-view stereo reconstruction algorithms. Until now, the lack of suitable calibrated multi-view image datasets with known ground truth (3D shape models) has prevented such direct comparisons. In this paper, we first survey multi-view stereo algorithms and compare them qualitatively using a taxonomy that differentiates their key properties. We then describe our process for acquiring and calibrating multiview image datasets with high-accuracy ground truth and introduce our evaluation methodology. Finally, we present the results of our quantitative comparison of state-of-the-art multi-view stereo reconstruction algorithms on six benchmark datasets. The datasets, evaluation details, and instructions for submitting new models are available online at http://vision.middlebury.edu/mview.
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“The presence of nonrigid or independent motion makes collecting a ground-truth dataset for optical flow far harder than for stereo, say, where structured light (Scharstein and Szeliski 2002) or range scanning (Seitz et al. 2006) can be used to obtain ground truth.”
From A Database and Evaluation Methodology for Optical Flow (2011) · cites this paper as Seitz et al. 2006
In the citing paper
“We also compute robust accuracy measures similar to those in Seitz et al. (2006): A X denotes the accuracy of the error measure at the Xth percentile, after sorting the errors from low to high.”
From A Database and Evaluation Methodology for Optical Flow (2011) · cites this paper as Seitz et al. (2006)
Citations
Cites
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
Self-citationA volumetric method for building complex models from range images
Curless, B., & Levoy, M. (1996) · Proceedings of the 23rd annual conference on Computer graphics and interactive techniques · doi:10.1145/237170.237269 · Cited by 3,124
Self-citationThe visual hull concept for silhouette-based image understanding
Laurentini, A. (1994) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.273735 · Cited by 1,470
High-quality video view interpolation using a layered representation
Zitnick, C. L., Kang, S. B., Uyttendaele, M., Winder, S. A. J., & Szeliski, R. (2004) · ACM Transactions on Graphics · doi:10.1145/1015706.1015766 · Cited by 1,386
Self-citationA 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 1,281
Self-citationOkutomi, M., & Kanade, T. (1993) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.206955 · Cited by 948
Multi-camera Scene Reconstruction via Graph Cuts
Kolmogorov, V., & Ramin Zabih, A. (2002) · Lecture notes in computer science · doi:10.1007/3-540-47977-5_6 · Cited by 745
Photorealistic Scene Reconstruction by Voxel Coloring
Seitz, S. M., & Dyer, C. R. (1999) · International Journal of Computer Vision · doi:10.1023/a:1008176507526 · Cited by 502
Self-citationA maximum-flow formulation of the N-camera stereo correspondence problem
Roy, S., & Cox, I. J. (2002) · International Conference on Computer Vision · doi:10.1109/iccv.1998.710763 · Cited by 489
Robust Parameter Estimation in Computer Vision
Stewart, C. V. (1999) · SIAM Review · doi:10.1137/s0036144598345802 · Cited by 455
Flagged first, then by citations
7 of the 70 references couldn’t be matched to a known paper.
Research works printed but not linked: 5
- zhang, 2001, Image-based multiresolution shape recovery by surface deformation, Videometrics Opt Meth 3D Shape Meas, 51
- seitz, 0, Multi-view Stereo Evaluation Web Page
- fromherz, 1995, Shape from multiple cues: Integrating local brightness information, ICYCS
- bouguet, 0, Camera Calibration Toolbox for MATLAB
- prock, 1998, Towards real-time voxel coloring, Image Understanding WS, 315
Cited by
Sorted by citations
Microsoft COCO: Common Objects in Context
Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., & Zitnick, C. L. (2014) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-10602-1_48 · Cited by 45,460
KinectFusion: Real-time dense surface mapping and tracking
Newcombe, R. A., Fitzgibbon, A., Izadi, S., Hilliges, O., Molyneaux, D., Kim, D., Davison, A. J., Kohi, P., Shotton, J., & Hodges, S. (2011) · 2011 10th IEEE International Symposium on Mixed and Augmented Reality · doi:10.1109/ismar.2011.6092378 · Cited by 4,008
DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation
Park, J. J., Florence, P., Straub, J., Newcombe, R., & Lovegrove, S. J. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.00025 · Cited by 3,789
Accurate, Dense, and Robust Multiview Stereopsis
Furukawa, Y., & Ponce, J. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2009.161 · Cited by 3,031
Pixelwise View Selection for Unstructured Multi-View Stereo
Schönberger, J. L., Zheng, E., Frahm, J., & Pollefeys, M. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-46487-9_31 · Cited by 2,331
Metadata
- Authors
- Seitz, S. M., Curless, B., Diebel, J., Scharstein, D., & Szeliski, R.
- Affiliations
- University of Washington (US)
- Stanford University (US)
- Middlebury College (US)
- Microsoft Research (United Kingdom) (GB)
- Venue
- 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (CVPR'06)
- Publisher
- IEEE
- Published
- 2006-07-10
- Volume
- 1
- Pages
- 519-528
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2160014001
- Cited by
- 2,457
- References
- 70
- Citations by year
- 2026: 60 · 2025: 94 · 2024: 118 · 2023: 131 · 2022: 94 · 2021: 142 · 2020: 134 · 2019: 129 · 2018: 116 · 2017: 150 · 2016: 146 · 2015: 149 · 2014: 177 · 2013: 151 · 2012: 157
- FWCI
- 70.73
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Physical Sciences › Earth and Planetary Sciences › Geology › 3D Surveying and Cultural Heritage
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › 3D Shape Modeling and Analysis
- Keywords
- multi-view stereo, 3D reconstruction, algorithm comparison, camera calibration, benchmark dataset, quantitative evaluation
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