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 image 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 trajectory in the pose space and the sparsity of occlusion in spatial domain to propose an optimization problem that not only registers the reference image to the observed distorted image but detects occlusions as well, both within a single framework. © 2014 Springer International Publishing.