Linearizing the Plenoptic Space

Gregoire Nieto, Frederic Devernay, James Crowley; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2017, pp. 1-12

The plenoptic function, also known as the light field or the lumigraph, contains the information about the radiance of all optical rays that go through all points in space in a scene. Since no camera can capture all this information, one of the main challenges in plenoptic imaging is light field reconstruction, which consists in interpolating the ray samples captured by the cameras to create a dense light field. Most existing methods perform this task by first attempting some kind of 3D reconstruction of the visible scene. Our method, in contrast, works by modeling the scene as a set of visual points, which describe how each point moves in the image when a camera moves. We compute visual point models of various degrees of complexity, and show that high-dimensional models are able to replicate complex optical effects such as reflection or refraction, and a model selection method can differentiate quasi-Lambertian from non-Lambertian areas in the scene.