by Peers, Pieter, Mahajan, Dhruv K., Lamond, Bruce, Ghosh, Abhijeet, Matusik, Wojciech, Ramamoorth, Ravi and Debevec, Paul
Abstract:
In this paper we propose a new framework for capturing light transport data of a real scene, based on the recently developed theory of compressive sensing. Compressive sensing offers a solid mathematical framework to infer a sparse signal from a limited number of non-adaptive measurements. Besides introducing compressive sensing for fast acquisition of light transport to computer graphics, we develop several innovations that address specific challenges for image-based relighting, and which may have broader implications. We develop a novel hierarchical decoding algorithm that improves reconstruction quality by exploiting inter-pixel coherency relations. Additionally, we design new non-adaptive illumination patterns that minimize measurement noise and further improve reconstruction quality. We illustrate our framework by capturing detailed high-resolution reflectance fields for image-based relighting.
Reference:
Compressive Light Transport Sensing (Peers, Pieter, Mahajan, Dhruv K., Lamond, Bruce, Ghosh, Abhijeet, Matusik, Wojciech, Ramamoorth, Ravi and Debevec, Paul), In ACM Transactions on Graphics, volume 28, 2009.
Bibtex Entry:
@article{peers_compressive_2009,
title = {Compressive {Light} {Transport} {Sensing}},
volume = {28},
url = {http://ict.usc.edu/pubs/Compressive%20Light%20Transport%20Sensing.pdf},
abstract = {In this paper we propose a new framework for capturing light transport data of a real scene, based on the recently developed theory of compressive sensing. Compressive sensing offers a solid mathematical framework to infer a sparse signal from a limited number of non-adaptive measurements. Besides introducing compressive sensing for fast acquisition of light transport to computer graphics, we develop several innovations that address specific challenges for image-based relighting, and which may have broader implications. We develop a novel hierarchical decoding algorithm that improves reconstruction quality by exploiting inter-pixel coherency relations. Additionally, we design new non-adaptive illumination patterns that minimize measurement noise and further improve reconstruction quality. We illustrate our framework by capturing detailed high-resolution reflectance fields for image-based relighting.},
number = {1},
journal = {ACM Transactions on Graphics},
author = {Peers, Pieter and Mahajan, Dhruv K. and Lamond, Bruce and Ghosh, Abhijeet and Matusik, Wojciech and Ramamoorth, Ravi and Debevec, Paul},
month = jan,
year = {2009},
keywords = {Graphics}
}