Methods and Applications for Portrait Selection from Video, Light Field Photography, and Light Field Video Editing

Abstract

Computational photography applications can assist photographers in capturing images that more closely represent a moment in time, a memory, or an artistic vision, compared to a traditional photograph. At the time of capture, computational cameras can record more information than traditional cameras. In post-processing, computational photography applications can selectively combine or edit down this information. In this thesis, I describe computational photography applications of this type. First, I describe a method to automatically select frames from video of a person that would work well as candid portraits. Next, I describe methods to render light field images from a consumer light field camera. In light field imaging, the scene is simultaneously photographed from multiple angles with a small baseline. The plane of focus and viewing angle can be decided in post-production, and small foreground objects or occluders can be removed. Finally, I describe possible applications of a future light field video camera, based on interviews with film industry professionals.