Efficient Multi-Scale Stereo of High-Resolution Planar and Spherical Images

In this paper we present a time- and space-efficient multi-scale method for stereo reconstruction from high-resolution planar and omnidirectional images. We first present the stereo algorithm and then extend it to omnidirectional images using a novel spherical disparity formulation. Our multi-scale method is based on a novel application of distance transforms to the disparity space images (DSI) at adjacent scales, without making hard, greedy decisions at coarser scales. We provide extensive experimental validation of our method using public benchmarks and demonstrate state-of-the-art performance for planar stereo and similar high-quality results for the spherical case.