Reconstructing mass-conserved water surfaces using shape from shading and optical flow

David Pickup, Chuan Li, Darren Cosker, Peter Hall, Philip Willis

Research output: Chapter in Book/Report/Conference proceedingChapter

15 Citations (Scopus)
140 Downloads (Pure)

Abstract

This paper introduces a method for reconstructing water from real video footage. Using a single input video, the proposed method produces a more informative reconstruction from a wider range of possible scenes than the current state of the art. The key is the combination of vision algorithms and physics laws. Shape from shading is used to capture the change of the water's surface, from which a vertical velocity gradient field is calculated. Such a gradient field is used to constrain the tracking of horizontal velocities by minimizing an energy function as a weighted combination of mass-conservation and intensity-conservation. Hence the final reconstruction contains a dense velocity field that is incompressible in 3D. The proposed method is efficient and performs consistently well across water of different types.
Original languageEnglish
Title of host publicationComputer Vision, ACCV 2010 - 10th Asian Conference on Computer Vision, Revised Selected Papers
Place of PublicationHeidelberg
PublisherSpringer
Pages189-201
Number of pages13
Volume6495 LNCS
ISBN (Print)0302-9743
DOIs
Publication statusPublished - 2011
Event10th Asian Conference on Computer Vision, ACCV 2010, November 8, 2010 - November 12, 2010 - Queenstown, New Zealand
Duration: 1 Jan 2011 → …

Conference

Conference10th Asian Conference on Computer Vision, ACCV 2010, November 8, 2010 - November 12, 2010
CountryNew Zealand
CityQueenstown
Period1/01/11 → …

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  • Cite this

    Pickup, D., Li, C., Cosker, D., Hall, P., & Willis, P. (2011). Reconstructing mass-conserved water surfaces using shape from shading and optical flow. In Computer Vision, ACCV 2010 - 10th Asian Conference on Computer Vision, Revised Selected Papers (Vol. 6495 LNCS, pp. 189-201). Springer. https://doi.org/10.1007/978-3-642-19282-1_16