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Reliable feature matching across widely separated views

Baumberg, A.·2002·Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662)

Abstract

We present a robust method for automatically matching features in images corresponding to the same physical point on an object seen from two arbitrary viewpoints. Unlike conventional stereo matching approaches we assume no prior knowledge about the relative camera positions and orientations. In fact in our application this is the information we wish to determine from the image feature matches. Features are detected in two or more images and characterised using affine texture invariants. The problem of window effects is explicitly addressed by our method-our feature characterisation is invariant to linear transformations of the image data including rotation, stretch and skew. The feature matching process is optimised for a structure-from-motion application where we wish to ignore unreliable matches at the expense of reducing the number of feature matches.

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Show all 3 references

Research works printed but not linked: 17

  1. kadyrov, 1995, Computer Analysis of Image and Patterns
  2. 10.1007/978-1-4757-6465-9 · DOI · Paper page
  3. 10.1016/S0262-8856(97)01144-X · DOI · Paper page
  4. 10.1007/BF01421488 · doi:10.1007/bf01421488
  5. 10.1109/ICCV.1998.710802 · DOI · Paper page
  6. 10.1007/BFb0028347 · doi:10.1007/bfb0028347
  7. schalkoff, 1989, Digital Image Processing and Computer Vision
  8. 10.1109/34.589215 · DOI · Paper page
  9. tomasi, 1994, Good features to track, CVPR94, 593
  10. faugeras, 1993, Three-Dimensional Computer Vision
  11. falkenhagen, 1994, Image Processing for Broadcast and Video Production, 115
  12. 10.1016/0031-3203(93)90098-H · DOI · Paper page
  13. gruen, 1985, Adaptive least squares correlation: A powerful image matching technique, Jornal of Photogrammetry Remote Sensing and Cartography, 14, 175
  14. 10.5244/C.12.37 · doi:10.5244/c.12.37
  15. deriche, 1994, Robust recovery of the epipolar geometry for an uncalibrated stereo rig, ECCV94, a:567
  16. beardsley, 1996, 3d model acquisition from extended image sequences, ECCV, 2, 683
  17. xu, 1997, A unified approach to image matching and segmentation in stereo, motion, and object recognition via recovery of epipolar geometry, Videre, 1, 22

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Metadata

Authors
Baumberg, A.
Venue
Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662)
Published
2002-11-07
Volume
1
Pages
774-781
ISSN
1063-6919 (ISSN-L)
OpenAlex
W2165497495
Cited by
627
References
3
FWCI
27.15
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Reliable feature matching across widely separated views. https://app.cochat.ai/papers/10.1109/cvpr.2000.855899
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Baumberg, A. (2002). Reliable feature matching across widely separated views. Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662). https://doi.org/10.1109/cvpr.2000.855899

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