Abstract

The coalesced presence of motion blur and rolling shutter effect is unavoidable due to the sequential exposure of sensor rows in CMOS cameras. We address the problem of detecting changes in an im- age affected by motion blur and rolling shutter artifacts with respect to a reference image. Our framework bundles modelling of motion blur in global shutter and rolling shutter cameras into a single entity. We leverage the sparsity of the camera tra jectory in the pose space and the sparsity of occlusion in spatial domain to propose an optimization prob- lem that not only registers the reference image to the observed distorted image but detects occlusions as well, both within a single framework.