• DocumentCode
    2239149
  • Title

    Computing correspondence based on regions and invariants without feature extraction and segmentation

  • Author

    Lee, Chi-Yin ; Cooper, David B. ; Keren, Daniel

  • Author_Institution
    Div. of Eng., Brown Univ., Providence, RI, USA
  • fYear
    1993
  • fDate
    15-17 Jun 1993
  • Firstpage
    655
  • Lastpage
    656
  • Abstract
    The problem addressed is the matching of corresponding regions in two images, even when the image intensity may be smoothly varying without distinctive edges. Corresponding small regions are assumed to be related by affine transformations. The matching is done by using a new class of low computational cost affine invariants. This approach also computes the affine transformation, and is ideal for applications to 3-D motion estimation and 3-D surface reconstruction, image alignment, etc. No feature extraction, segmentation or epipolar constraint is required. The advantage of the authors´ approach over area matching is that it handles large baselines, i.e., the distance between camera positions, where the differences in orientation and linear distortion of two areas being compared is large
  • Keywords
    computational complexity; image sequences; 3-D motion estimation; 3-D surface reconstruction; affine transformations; image alignment; image correspondence; image region matching; invariants; low computational cost affine invariants; regions; smoothly varying image intensity; Cameras; Computational efficiency; Feature extraction; Gold; Image reconstruction; Image segmentation; Laboratories; Motion estimation; Surface reconstruction; Systems engineering and theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 1993. Proceedings CVPR '93., 1993 IEEE Computer Society Conference on
  • Conference_Location
    New York, NY
  • ISSN
    1063-6919
  • Print_ISBN
    0-8186-3880-X
  • Type

    conf

  • DOI
    10.1109/CVPR.1993.341042
  • Filename
    341042