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
Link To Document :
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