Deep Light Source Estimation for Mixed Reality

Bruno Augusto Dorta Marques, Rafael Rego Drumond, Cristina Nader Vasconcelos, Esteban Clua

2018

Abstract

Mixed reality is the union of virtual and real elements in a single scene. In this composition, of real and virtual elements, perceptual discrepancies in the illumination of objects may occur. We call these discrepancies the illumination mismatch problem. Recovering the lighting information from a real scene is a difficult task. Usually, such task requires prior knowledge of the scene, such as the scene geometry and special measuring equipment. We present a deep learning based technique that estimates point light source position from a single color image. The estimated light source position is used to create a composite image containing both the real and virtual environments. The proposed technique allows the final composite image to have consistent illumination between the real and virtual worlds, effectively reducing the effects of the illumination mismatch in Mixed Reality applications.

Paper Citation

in Harvard Style

Marques B., Drumond R., Vasconcelos C. and Clua E. (2018). Deep Light Source Estimation for Mixed Reality. In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 1: GRAPP; ISBN 978-989-758-287-5, SciTePress, pages 303-311. DOI: 10.5220/0006724303030311

in Bibtex Style

@conference{grapp18,
author={Bruno Augusto Dorta Marques and Rafael Rego Drumond and Cristina Nader Vasconcelos and Esteban Clua},
title={Deep Light Source Estimation for Mixed Reality},
booktitle={Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 1: GRAPP},
year={2018},
pages={303-311},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006724303030311},
isbn={978-989-758-287-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 1: GRAPP
TI - Deep Light Source Estimation for Mixed Reality
SN - 978-989-758-287-5
AU - Marques B.
AU - Drumond R.
AU - Vasconcelos C.
AU - Clua E.
PY - 2018
SP - 303
EP - 311
DO - 10.5220/0006724303030311
PB - SciTePress