Discovering Point Lights with Intensity Distance Fields
Edward Zhang1 Michael F. Cohen2 Brian Curless1
1 University of Washington 2 Facebook Inc.
CVPR 2018
Abstract
We introduce the light localization problem. A scene is illuminated by a set of unobserved isotropic point lights. Given the geometry, materials, and illuminated appearance of the scene, the light localization problem is to completely recover the number, positions, and intensities of the lights. We first present a scene transform that identifies likely light positions. Based on this transform, we develop an iterative algorithm to locate remaining lights and determine all light intensities. We demonstrate the success of this method in a large set of 2D synthetic scenes, and show that it extends to 3D, in both synthetic scenes and real-world scenes.Paper
Edward Zhang, Michael F. Cohen, and Brian Curless. 2018.
"Discovering Point Lights with Intensity Distance Fields"
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018
( PDF | Supplementary | BibTex )
"Discovering Point Lights with Intensity Distance Fields"
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018
( PDF | Supplementary | BibTex )
Acknowledgements
This work was supported by the NSF/Intel Visual and Experiential Computing Award #1538618, with additional support from Google and the University of Washington Reality Lab.