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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Aguiar, E.D., Stoll, C., Theobalt, C., Ahmed, N., Seidel, H., Thrun, S.: Performance capture from sparse multi-view video. In: Proceedings of ACM SIGGRAPH, vol. 27, pp. 1–10 (2008)
Atcheson, B., Ihrke, I., Heidrich, W., Tevs, A., Bradley, D., Magnor, M., Seidel, H.: Time-resolved 3d capture of non-stationary gas flows. In: Proceedings of ACM SIGGRAPH Asia, vol. 27, pp. 1–9 (2008)
Balschbach, G., Klinke, J., Jähne, B.: Multichannel shape from shading techniques for moving specular surfaces. In: Burkhardt, H., Neumann, B. (eds.) ECCV 1998. LNCS, vol. 1407, pp. 170–184. Springer, Heidelberg (1998)
Ding, Y.Y., Yu, J.Y., Sturm, P.: Recovering specular surfaces using curved line images. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2326–2333 (2009)
Doshi, A., Bors, A.G.: Navier-stokes formulation for modelling turbulent optical flow. In: Proceedings of the British Machine Vision Conference, pp. 1–10 (2007)
Ghosh, A., Hawkins, T., Peers, P., Frederiksen, S., Debevec, P.: Practical modeling and acquisition of layered facial reflectance. In: Proceedings of ACM SIGGRAPH Asia, vol. 27, pp. 1–10 (2008)
Héas., P., Mémin, E.: Three-dimensional motion estimation of atmospheric layers from image sequences, vol. 46, pp. 2385–2396 (2008)
Hilsenstein, V.: Surface reconstruction of water waves using thermographic stereo imaging. In: Image and Vision Computing, New Zealand, pp. 102–107 (2005)
Horn, B.K.P., Schunck, B.G.: Determing optical flow. Artificial Intelligence 17, 185–203 (1981)
Ihrke, I., Goldluecke, B., Magnor, M.: Reconstructing the geometry of flowing water. In: Proceedings of the International Conference on Computer Vision, pp. 1055–1060 (2005)
Li, F., Xu, L.W., Guyenne, P., Yu, J.Y.: Recovering fluid-type motions using navier-stokes potential flow. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (2010)
Morris, N.J., Kutulakos, K.N.: Dynamic refraction stereo. In: Proceedings of the International Conference on Computer Vision, pp. 1573–1580 (2005)
Murase, H.: Surface shape reconstruction of a nonrigid transport object using refraction and motion. IEEE Transactions on Pattern Analysis and Machine Intelligence 14, 1045–1052 (1992)
Nakajima, Y., Inomata, H., Nogawa, H., Sato, Y., Tamura, S., Okazaki, K., Torii, S.: Physics-based flow estimation of fluids. Pattern Recgonition 36, 1203–1212 (2003)
Papadakis, N., Héas, P., Mémin, E.: Image assimilation for motion estimation of atmospheric layers with shallow-water model. In: Proceedings of the Asia Conference on Computer Vision, pp. 864–874 (2007)
Paris, S., Chang, W., Kozhushnyan, O.I., Jarosz, W., Matusik, W., Zwicker, M., Durand, F.: Hair photobooth: geometric and photometric acquisition of real hairstyles. In: Proceedings of ACM SIGGRAPH, pp. 1–9. ACM, New York (2008)
Péteri, R., Fazekas, S., Huiskes, M.J.: Dyntex: a comprehensive database of dynamic textures. Pattern Recognition Letters (2010)
Sakaino, H.: Motion estimation method based on physical properties of waves. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2008)
Shand, T., Shand, R., Bailey, D., Andrews, C.: Wave deformation in the vicinity of a long ocean outfall at wanganui, new zealand. In: Coasts and Ports Australasian Conference, pp. 173–178 (2005)
Tan, P., Fang, T., Xiao, J.X., Zhao, P., Quan, L.: Single image tree modeling. In: Proceedings of ACM SIGGRAPH, Asia, vol. 27, pp. 1–7 (2008)
Tan, P., Zeng, G., Wang, J.D., Kang, S.B., Quan, L.: Image-based tree modeling. In: Proceedings of ACM SIGGRAPH, vol. 87. ACM, New York (2007)
Tsai, P., Shah, M.: Shape from shading using linear approximation. Image and Vision Computing 12, 487–498 (1994)
Wang, H.M., Liao, M., Zhang, Q., Yang, R.G., Turk, G.: Physically guided liquid surface modeling from videos. In: Proceedings of ACM SIGGRAPH, pp. 1–11 (2009)
Zhang, R., Tsai, P.S., Cryer, J.E., Shah, M.: Shape from shading: A survey. IEEE Transactions on Pattern Analysis and Machine Intelligence 21, 690–706 (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pickup, D., Li, C., Cosker, D., Hall, P., Willis, P. (2011). Reconstructing Mass-Conserved Water Surfaces Using Shape from Shading and Optical Flow. In: Kimmel, R., Klette, R., Sugimoto, A. (eds) Computer Vision – ACCV 2010. ACCV 2010. Lecture Notes in Computer Science, vol 6495. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19282-1_16
Download citation
DOI: https://doi.org/10.1007/978-3-642-19282-1_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19281-4
Online ISBN: 978-3-642-19282-1
eBook Packages: Computer ScienceComputer Science (R0)