Compressive Light Transport Sensing (bibtex)
by Pieter Peers, Dhruv K. Mahajan, Bruce Lamond, Abhijeet Ghosh, Wojciech Matusik, Ravi Ramamoorth, Paul Debevec
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 (Pieter Peers, Dhruv K. Mahajan, Bruce Lamond, Abhijeet Ghosh, Wojciech Matusik, Ravi Ramamoorth, Paul Debevec), 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}
}
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