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Optical computing for fast light transport analysis

Published:15 December 2010Publication History
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Abstract

We present a general framework for analyzing the transport matrix of a real-world scene at full resolution, without capturing many photos. The key idea is to use projectors and cameras to directly acquire eigenvectors and the Krylov subspace of the unknown transport matrix. To do this, we implement Krylov subspace methods partially in optics, by treating the scene as a "black box subroutine" that enables optical computation of arbitrary matrix-vector products. We describe two methods---optical Arnoldi to acquire a low-rank approximation of the transport matrix for relighting; and optical GMRES to invert light transport. Our experiments suggest that good quality relighting and transport inversion are possible from a few dozen low-dynamic range photos, even for scenes with complex shadows, caustics, and other challenging lighting effects.

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  • Published in

    cover image ACM Transactions on Graphics
    ACM Transactions on Graphics  Volume 29, Issue 6
    December 2010
    480 pages
    ISSN:0730-0301
    EISSN:1557-7368
    DOI:10.1145/1882261
    Issue’s Table of Contents

    Copyright © 2010 ACM

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    Publication History

    • Published: 15 December 2010
    Published in tog Volume 29, Issue 6

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