2-point RANSAC for scene image matching under large viewpoint changes

This work aims to accurately match two scene images under large viewpoint changes, which is the key issue in appearance-based localization tasks. In this paper, two key ideas are proposed to solve the challenging problem. First, to detect extreme small overlapping regions between two images, a new approach is developed to estimate the camera motion using only two pairs of matched features, while the state-of-art needs at least five. Second, proper prior knowledge to the environmental structures is utilized to strengthen the outlier rejection. The proposed 2-point approach is tested on challenging scenes and shows good robustness to the drastic occlusion and scaling caused by viewpoint changes.