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Robust Wide Baseline Stereo from Maximally Stable Extremal Regions
Abstract
Abstract The wide-baseline stereo problem, i.e. the problem of establishing correspondences between a pair of images taken from different viewpoints is studied. A new set of image elements that are put into correspondence, the so called extremal regions , is introduced. Extremal regions possess highly desirable properties: the set is closed under (1) continuous (and thus projective) transformation of image coordinates and (2) monotonic transformation of image intensities. An efficient (near linear complexity) and practically fast detection algorithm (near frame rate) is presented for an affinely invariant stable subset of extremal regions, the maximally stable extremal regions (MSER). A new robust similarity measure for establishing tentative correspondences is proposed. The robustness ensures that invariants from multiple measurement regions (regions obtained by invariant constructions from extremal regions), some that are significantly larger (and hence discriminative) than the MSERs, may be used to establish tentative correspondences. The high utility of MSERs, multiple measurement regions and the robust metric is demonstrated in wide-baseline experiments on image pairs from both indoor and outdoor scenes. Significant change of scale (3.5×), illumination conditions, out-of-plane rotation, occlusion, locally anisotropic scale change and 3D translation of the viewpoint are all present in the test problems. Good estimates of epipolar geometry (average distance from corresponding points to the epipolar line below 0.09 of the inter-pixel distance) are obtained.
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Metadata
- Authors
- Matas, J., Chum, O., Urban, M., & Pajdla, T.
- Affiliations
- University of Surrey (GB)
- Venue
- Procedings of the British Machine Vision Conference 2002
- Publisher
- British Machine Vision Association
- Published
- 2002
- Pages
- 36.1-36.10
- OpenAlex
- W2147237076
- Cited by
- 1,350
- References
- 15
- Citations by year
- 2026: 4 · 2025: 8 · 2024: 11 · 2023: 6 · 2022: 17 · 2021: 23 · 2020: 34 · 2019: 56 · 2018: 61 · 2017: 74 · 2016: 118 · 2015: 125 · 2014: 96 · 2013: 89 · 2012: 82
- FWCI
- 8.63
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- British Machine Vision Conference (BMVC) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
- Keywords
- wide-baseline stereo, MSER, feature detection, correspondence estimation, affine invariance, projective invariance, epipolar geometry estimation, scale variation, illumination variation, occlusion
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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