Find a large number of reliable point correspondences for fish-eye images

In this paper, we propose a new approach to find a large number of reliable point features between high distorted stereo fisheye images, which is very valuable in many applications, such as image-based metrology, geometry estimation and 3D reconstruction. In first step the affine invariant regions are matched by classical approaches then distinctive points within the region can be matched based on the corresponding affine transformations in normalized frames. In addition, two distinctive point matching algorithms are proposed, one is based on the intensity similarity measure, and the others is based on the geometric consistency constraint. Experiment results show that the number of the final point correspondences increased greatly with high accuracy and reliability. This electronic document is a “live” template. The various components of your paper [title, text, heads, etc.] are already defined on the style sheet, as illustrated by the portions given in this document.