Light Field Editing and Rendering
Matthieu Hog · HAL (Le Centre pour la Communication Scientifique Directe) · 2018
By imaging a scene from different viewpoints, a light field allows capturing a lot of information about the scene geometry. Thanks to the recent development of its acquisition devices (plenoptic camera and camera arrays mainly), light field imaging is becoming a serious alternative for 3D content capture and other related problems. The goal of this thesis is twofold. One of the main application for light field imaging is its ability to produce new views from a single capture. In a first part, we propose new image rendering techniques in two cases that deviate from the mainstream light field image rendering. We first propose a full pipeline for focused plenoptic cameras, addressing calibration, depth estimation, and image rendering. We then move to the problem of view synthesis, we seek to generate intermediates views given a set of only 4 corner views of a light field. Image editing is a common step of media production. For 2D images and videos, a lot of commercial tools exist. However, the problem is rather unexplored for light fields. In a second part, we propose new and efficient light field editing techniques. We first propose a new graph-based pixel-wise segmentation method that, from a sparse set of user input, segments simultaneously all the views of a light field. Then we propose an automatic light field over-segmenting approach that makes use of GPUs computational power. This approach further decreases the computational requirement for light field segmentation and we extend the approach for light field video segmentation.