The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Evaluation of Cost Functions for Stereo Matching
Abstract
Stereo correspondence methods rely on matching costs for computing the similarity of image locations. In this paper we evaluate the insensitivity of different matching costs with respect to radiometric variations of the input images. We consider both pixel-based and window-based variants and measure their performance in the presence of global intensity changes (e.g., due to gain and exposure differences), local intensity changes (e.g., due to vignetting, non-Lambertian surfaces, and varying lighting), and noise. Using existing stereo datasets with ground-truth disparities as well as six new datasets taken under controlled changes of exposure and lighting, we evaluate the different costs with a local, a semi-global, and a global stereo method.
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Cites
Fast approximate energy minimization via graph cuts
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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-citationAn experimental comparison of min-cut/max- flow algorithms for energy minimization in vision
Boykov, Y., & Kolmogorov, V. (2004) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2004.60 · Cited by 4,577
What energy functions can be minimized via graph cuts?
Kolmogorov, V., & Zabih, R. (2004) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2004.1262177 · Cited by 3,127
Alignment by Maximization of Mutual Information
Viola, P., & Wells III, W. M. (1997) · International Journal of Computer Vision · doi:10.1023/a:1007958904918 · Cited by 2,610
Non-parametric local transforms for computing visual correspondence
Zabih, R., & Woodfill, J. (1994) · Lecture Notes in Computer Science · doi:10.1007/bfb0028345 · Cited by 1,763
Accurate and Efficient Stereo Processing by Semi-Global Matching and Mutual Information
Hirschmuller, H. (2005) · 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) · doi:10.1109/cvpr.2005.56 · Cited by 1,698
Self-citationHigh-accuracy stereo depth maps using structured light
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Self-citationHigh-quality video view interpolation using a layered representation
Zitnick, C. L., Kang, S. B., Uyttendaele, M., Winder, S., & Szeliski, R. (2004) · ACM Transactions on Graphics · doi:10.1145/1015706.1015766 · Cited by 1,385
Adaptive support-weight approach for correspondence search
Yoon, K.-J., & Kweon, I. S. (2006) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2006.70 · Cited by 1,194
Cited by
Fattal, R. (2008) · ACM Transactions on Graphics · doi:10.1145/1360612.1360671 · Cited by 2,114
MVSNet: Depth Inference for Unstructured Multi-view Stereo
Yao, Y., Luo, Z., Li, S., Fang, T., & Quan, L. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01237-3_47 · Cited by 1,455
A Multi-view Stereo Benchmark with High-Resolution Images and Multi-camera Videos
Schops, T., Schonberger, J. L., Galliani, S., Sattler, T., Schindler, K., Pollefeys, M., & Geiger, A. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.272 · Cited by 915
A Real-Time Low-Power Stereo Vision Engine Using Semi-Global Matching
Gehrig, S. K., Eberli, F., & Meyer, T. (2009) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-04667-4_14 · Cited by 270
Dehazing Evaluation: Real-World Benchmark Datasets, Criteria, and Baselines
Zhao, S., Zhang, L., Huang, S., Shen, Y., & Zhao, S. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.2995264 · Cited by 169
Metadata
- Authors
- Hirschmuller, H., & Scharstein, D.
- Venue
- 2007 IEEE Conference on Computer Vision and Pattern Recognition
- Publisher
- IEEE
- Published
- 2007-06
- Pages
- 1-8
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2133255058
- Cited by
- 1,122
- References
- 19
- FWCI
- 27.64
- Type
- conference paper
- Language
- en
- Open access
- closed
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