Stereo Rectification

Stereo rectification is the process of transforming two images from a stereo camera pair (or other multi-view systems) so that corresponding points lie on the same horizontal scanline, simplifying depth estimation. Current research focuses on improving rectification accuracy and robustness, particularly for challenging scenarios like those involving rotating cameras, rolling shutter artifacts, or limited baseline distances. This involves developing novel algorithms, often leveraging techniques like diffusion models or bidirectional alignment, and creating new datasets for training and evaluation. Advances in stereo rectification are crucial for applications ranging from autonomous navigation and 3D modeling to augmented and virtual reality, enabling more accurate and efficient depth perception in various contexts.