Lens flares are a common optical artifact in photography and filmmaking caused by reflections and scattering within a camera system. While they can degrade image quality, lens flares are sometimes harnessed artistically to enhance visual appeal. This reasearch captures lens flares using a motion control setup. It harnesses image based and machine learning interpolation techniques to represent the flare artifacsts faithfully in compositing.
A portion of the dataset is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Download: https://degas.filmakademie.de/nextcloud/s/74i68PTrwimswyg
Password: HtaqxrFWkY
@inproceedings{10.1145/3681758.3697995,
author = {Maurer, Vincent},
title = {Capturing Light with Robots: A Novel Workflow for Reproducing Realistic Lens Flares},
year = {2024},
isbn = {9798400711404},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3681758.3697995},
doi = {10.1145/3681758.3697995},
abstract = {Lens flares are a common optical artifact in photography and filmmaking caused by reflections and scattering of light within a camera system. The task of creating lens flares is usually solved with 2D approaches or simulation. This research compares two alternative methods of reproducing lens flares for a production-ready compositing workflow: traditional image processing and machine learning techniques. To create the dataset, a novel approach to capturing lens flares in a grid-like manner is explored. By systematically varying the position of a light source with a motion control system, flare patterns for a diverse set of lenses are captured.},
booktitle = {SIGGRAPH Asia 2024 Technical Communications},
articleno = {20},
numpages = {4},
keywords = {Lens Flares, Visual Effects, Compositing, Motion Control, Machine Learning},
location = {
},
series = {SA '24}
}