Compressive Light Transport Sensing (bibtex)
by Pieter Peers, Dhruv K. Mahajan, Bruce Lamond, Abhijeet Ghosh, Wojciech Matusik, Ravi Ramamoorthi, Paul Debevec
Abstract:
In this paper we propose a new framework for capturing light trans- port data of a real scene, based on the recently developed theory of compressive sensing. Compressive sensing offers a solid math- ematical 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 Ramamoorthi, Paul Debevec), 2008.
Bibtex Entry:
@techreport{peers_compressive_2008,
	type = {{ICT} {Technical} {Report}},
	title = {Compressive {Light} {Transport} {Sensing}},
	url = {http://ict.usc.edu/pubs/ICT%20TR%2005%202008.pdf},
	abstract = {In this paper we propose a new framework for capturing light trans- port data of a real scene, based on the recently developed theory of compressive sensing. Compressive sensing offers a solid math- ematical 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 = {ICT TR 05 2008},
	institution = {University of Southern California Institute for Creative Technologies},
	author = {Peers, Pieter and Mahajan, Dhruv K. and Lamond, Bruce and Ghosh, Abhijeet and Matusik, Wojciech and Ramamoorthi, Ravi and Debevec, Paul},
	year = {2008},
	keywords = {Graphics}
}
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