Motion aware motion invariance
Scott McCloskey, Kelly Muldoon, Sharath Venkatesha · 2014
We address motion de-blurring using a computational camera that captures an image while the stabilizing optical element moves in a modified Canon IS lens. Our work builds on that of Levin et al. [11], who introduce parabolic motion as a means of achieving invariance to unknown subject velocity in an a priori known direction. While the previous work addresses a specific scenario - exact knowledge of motion orientation and a uniform, symmetric prior on its magnitude - we generalize this to address scenarios where the motion of objects in the scene or the camera itself are known to various extents. We describe a motion invariant camera based on an off-the-shelf lens, and show how its motion and position sensors can be used to inform both the image capture and de-blurring. We demonstrate that our changes to motion invariance improve the quality of captured images in the case of both object and camera motion.