Compressive Dual Photography

dc.contributor.authorSen, Pradeepen_US
dc.contributor.authorDarabi, Soheilen_US
dc.date.accessioned2015-02-23T10:17:29Z
dc.date.available2015-02-23T10:17:29Z
dc.date.issued2009en_US
dc.description.abstractThe accurate measurement of the light transport characteristics of a complex scene is an important goal in computer graphics and has applications in relighting and dual photography. However, since the light transport data sets are typically very large, much of the previous research has focused on adaptive algorithms that capture them efficiently. In this work, we propose a novel, non-adaptive algorithm that takes advantage of the compressibility of the light transport signal in a transform domain to capture it with less acquisitions than with standard approaches. To do this, we leverage recent work in the area of compressed sensing, where a signal is reconstructed from a few samples assuming that it is sparse in a transform domain. We demonstrate our approach by performing dual photography and relighting by using a much smaller number of acquisitions than would normally be needed. Because our algorithm is not adaptive, it is also simpler to implement than many of the current approaches.en_US
dc.description.number2en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume28en_US
dc.identifier.doi10.1111/j.1467-8659.2009.01401.xen_US
dc.identifier.issn1467-8659en_US
dc.identifier.pages609-618en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2009.01401.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltden_US
dc.titleCompressive Dual Photographyen_US
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