DocumentCode
2536950
Title
Automatic line matching across views
Author
Schmid, Cordelia ; Zisserman, Andrew
Author_Institution
Dept. of Eng. Sci., Oxford Univ., UK
fYear
1997
fDate
17-19 Jun 1997
Firstpage
666
Lastpage
671
Abstract
The paper presents a new method for matching individual line segments between images. The method uses both grey-level information and the multiple view geometric relations between the images. For image pairs epipolar geometry facilitates the computation of a cross-correlation based matching score for putative line correspondences. For image triplets cross-correlation matching scores are used in conjunction with line transfer based on the trifocal geometry. Algorithms are developed for both short and long range motion. In the case of long range motion the algorithm involves evaluating a one parameter family of plane induced homographies. The algorithms are robust to deficiencies in the line segment extraction and partial occlusion. Experimental results are given for image pairs and triplets, for varying motions between views, and for different scene types. The three view algorithm eliminates all mismatches
Keywords
computational geometry; edge detection; image matching; motion estimation; automatic line matching; cross-correlation based matching score; epipolar geometry; grey-level information; image pairs; image triplets; individual line segment matching; line segment extraction; line transfer; long range motion; multiple view geometric relations; partial occlusion; plane induced homographies; putative line correspondences; scene types; short range motion; three view algorithm; trifocal geometry; views; Cameras; Geometry; Image reconstruction; Image segmentation; Layout; Marine vehicles; Robustness; Shape; Surface reconstruction;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition, 1997. Proceedings., 1997 IEEE Computer Society Conference on
Conference_Location
San Juan
ISSN
1063-6919
Print_ISBN
0-8186-7822-4
Type
conf
DOI
10.1109/CVPR.1997.609397
Filename
609397
Link To Document