Benoit Vandame

An Image Rendering Pipeline for Focused Plenoptic Cameras

In this paper, we present a complete processing pipeline for focused plenoptic cameras. In particular, we propose 1) a new algorithm for microlens center calibration fully in the Fourier domain, 2) a novel algorithm for depth map computation using a stereo focal stack, and 3) a depth-based rendering algorithm that is able to refocus at a particular depth or to create all-in-focus images. The proposed algorithms are fast, accurate, and do not need to generate subaperture images or epipolar plane images which is capital for focused plenoptic cameras. Also, the resolution of the resulting depth map is the same as the rendered image. We show results of our pipeline on Georgievs dataset and real images captured with different Raytrix cameras.

Dataset and Pipeline for Multi-view Light-Field Video

The quantity and diversity of data in Light-Field videos makes this content valuable for many applications such as mixed and augmented reality or post-production in the movie industry. Some of such applications require a large parallax between the different views of the Light-Field, making the multi-view capture a better option than plenoptic cameras. In this paper we propose a dataset and a complete pipeline for Light-Field video. The proposed algorithms are specially tailored to process sparse and wide-baseline multi-view videos captured with a camera rig. Our pipeline includes algorithms such as geometric calibration, color homogenization, view pseudo-rectification and depth estimation. Such elemental algorithms are well known by the state-of-the-art but they must achieve high accuracy to guarantee the success of other algorithms using our data. Along this paper, we publish our Light-Field video dataset that we believe may be of special interest for the community. We provide the original sequences, the calibration parameters and the pseudo-rectified views. Finally, we propose a depth-based rendering algorithm for Dynamic Perspective Rendering.