Light fields imaging technologies

Light fields capture all light rays passing through a given volume of space.
Compared to traditional 2D imaging systems which capture the spatial intensity of the light rays, 4D light fields also contain the angular direction of light rays.
This additional information allows for multiple applications in different research areas such as image processing, computer vision, and computer graphics, including (but not limited to) the reconstruction of the 3D geometry of a scene, creating new images from virtual point of view, or changing the focus of an image after it is captured.
Light fields are also a growing topic of interest in the VR/AR community.

Below is an example of a light field captured with a Lytro Illum camera, which allows for refocusing and changing the perspective.

In V-SENSE, we are currently investigating novel methods for light field denoising, scene reconstruction from light field, and light field rendering.



Ganter, David; Alain, Martin; Hardman, David; Smolic, Aljoscha; Manzke, Michael

Light-Field Volume Rendering on GPU for Streaming Time-Varying Data Conference

Pacific Graphics (PG 2018), 2018.


Alain, Martin; Smolic, Aljosa

Light Field Super-Resolution via LFBM5D Sparse Coding Conference

IEEE International Conference on Image Processing (ICIP 2018), 2018.

Abstract | Links | BibTeX

Matysiak, Pierre; Grogan, Mairéad; Le Pendu, Mikaël ; Alain, Martin; Smolic, Aljosa

A Pipeline for Lenslet Light Field Quality Enhancement Conference Forthcoming

IEEE International Conference on Image Processing (ICIP 2018), Forthcoming.

Abstract | Links | BibTeX

Le Pendu, Mikael ; Guillemot, Christine; Smolic, Aljosa

High Dynamic Range Light Fields via Weighted Low Rank Approximation Conference

IEEE International Conference on Image Processing (ICIP 2018), 2018.

Abstract | Links | BibTeX


Alain, Martin; Smolic, Aljosa

Light Field Denoising by Sparse 5D Transform Domain Collaborative Filtering Inproceedings

IEEE International Workshop on Multimedia Signal Processing (MMSP 2017) - Top 10% Paper Award, 2017.

Abstract | Links | BibTeX

Chen, Yang; Alain, Martin; Smolic, Aljosa

Fast and Accurate Optical Flow based Depth Map Estimation from Light Fields Inproceedings

Irish Machine Vision and Image Processing Conference (Received the Best Paper Award), 2017.

Abstract | Links | BibTeX

This entry was posted in Light-Fields and tagged by Martin Alain. Bookmark the permalink.

About Martin Alain

Martin Alain is currently a postdoctoral researcher in the V-SENSE project at the School of Computer Science and Statistics in Trinity College Dublin. He received the Master’s degree in electrical engineering from the Bordeaux Graduate School of Engineering (ENSEIRB-MATMECA), Bordeaux, France in 2012 and the PhD degree in signal processing and telecommunications from University of Rennes 1, Rennes, France in 2016. As a PhD student working in Technicolor and INRIA in Rennes, France, he explored novel image and video compression algorithms. His research interests lie at the intersection of signal and image processing, computer vision, and computer graphics. His current research topic involves light field imaging, with a focus on denoising, super-resolution, compression, scene reconstruction, and rendering.