Robust Image Matching under a Large Disparity
Yasushi Kanazawa, Kenichi Kanatani · Institutional Repositories DataBase (IRDB) · 2002
We present a new method for detecting point matches between two images that have a large disparity resulting from camera rotations and zooming changes. Our strategy is to impose various constraints such as local image correlations, spatial consistency, and global smoothness as “soft ” constraints via their “confidence ” before imposing the “hard” epipolar constraint by RANSAC. We also introduce a model selection procedure to test if the image mapping can be regarded as a homography. We demonstrate the effectiveness of our method by real image examples. 1.