Robust Feature Matching for Distorted Projection by Spherical Cameras

In this work, we proposes a simple yet effective method for improving performance of local feature matching among equirectangular cylindrical images, which brings more stable and complete 3D reconstruction by incremental SfM. The key idea is to exiplictly generate synthesized images by rotating the spherical panoramic images and to detect and describe features only from the less distroted area in the rectified panoramic images. We demonstrate that the proposed method is advantageous for both rotational and translational camera motions compared with the standard methods on the synthetic data. We also demonstrate that the proposed feature matching is beneficial for incremental SfM through the experiments on the Pittsburgh Reserach dataset.