ROLLING SHUTTER RECTIFICATION IN IMAGES/VIDEOS USING CONVOLUTIONAL NEURAL NETWORKS WITH APPLICATIONS TO SFM/SLAM WITH ROLLING SHUTTER IMAGES/VIDEOS

摘要

A method for correcting rolling shutter (RS) effects is presented. The method includes generating a plurality of images from a camera, synthesizing RS images from global shutter (GS) counterparts to generate training data to train the structure-and-motion-aware convolutional neural network (CNN), and predicting an RS camera motion and an RS depth map from a single RS image by employing a structure-and-motion-aware CNN to remove RS distortions from the single RS image.