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.
Index Terms:
image matching; automatic line matching; views; individual line segment matching; grey-level information; multiple view geometric relations; image pairs; epipolar geometry; cross-correlation based matching score; putative line correspondences; image triplets; line transfer; trifocal geometry; short range motion; long range motion; plane induced homographies; line segment extraction; partial occlusion; scene types; three view algorithm
Citation:
C. Schmid, A. Zisserman, "Automatic line matching across views," cvpr, pp.666, 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'97), 1997