“Time-resolved 3d capture of non-stationary gas flows”
Conference:
Type(s):
Title:
- Time-resolved 3d capture of non-stationary gas flows
Session/Category Title: Image-based capture
Presenter(s)/Author(s):
Abstract:
Fluid simulation is one of the most active research areas in computer graphics. However, it remains difficult to obtain measurements of real fluid flows for validation of the simulated data.In this paper, we take a step in the direction of capturing flow data for such purposes. Specifically, we present the first time-resolved Schlieren tomography system for capturing full 3D, non-stationary gas flows on a dense volumetric grid. Schlieren tomography uses 2D ray deflection measurements to reconstruct a time-varying grid of 3D refractive index values, which directly correspond to physical properties of the flow. We derive a new solution for this reconstruction problem that lends itself to efficient algorithms that robustly work with relatively small numbers of cameras. Our physical system is easy to set up, and consists of an array of relatively low cost rolling-shutter camcorders that are synchronized with a new approach. We demonstrate our method with real measurements, and analyze precision with synthetic data for which ground truth information is available.
References:
1. Agrawal, A., Albers, B., and Griffin, D. 1999. Abel inversion of Deflectometric Measurements in Dynamic Flows. Applied Optics 38, 15 (May), 3394–3398.Google ScholarCross Ref
2. Agrawal, A., Raskar, R., and Chellappa, R. 2006. What Is the Range of Surface Reconstructions from a Gradient Field? In Proc. ECCV, 578–591. Google Scholar
3. Atcheson, B., Heidrich, W., and Ihrke, I. 2008. An Evaluation of Optical Flow Algorithms for Background Oriented Schlieren Imaging. Experiments in Fluids. in print.Google Scholar
4. Barrett, R., Berry, M., Chan, T. F., Demmel, J., Donato, J., Dongarra, J., Eijkhout, V., Pozo, R., Romine, C., and der Vorst, H. V. 1994. Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods, 2nd Edition. SIAM, Philadelphia, PA.Google Scholar
5. Ben-Ezra, M., and Nayar, S. 2003. What Does Motion Reveal about Transparency? In Proc. ICCV, vol. 2, 1025–1032. Google ScholarDigital Library
6. Brox, T., Bruhn, A., Papenberg, N., and Weickert, J. 2004. High Accuracy Optical Flow Estimation Based on a Theory for Warping. In Proc. ECCV, 25–36.Google Scholar
7. Chuang, Y., Zongker, D., Hindorff, J., Curless, B., Salesin, D., and Szeliski, R. 2000. Environment Matting Extensions: Towards Higher Accuracy and Real-Time Capture. In Proc. SIGGRAPH, 121–130. Google Scholar
8. Cook, R., and DeRose, T. 2005. Wavelet Noise. ACM Trans. Graphics (Proc. SIGGRAPH) 24, 3 (July), 803–811. Google ScholarDigital Library
9. Dalziel, S., Hughes, G., and Sutherland, B. 2000. Whole-Field Density Measurements by ‘Synthetic Schlieren’. Experiments in Fluids 28, 322–335.Google ScholarCross Ref
10. de Aguiar, E., Stoll, C., Theobalt, C., Ahmed, N., Seidel, H.-P., and Thrun, S. 2008. Performance Capture from Sparse Multi-view Video. ACM Trans. Graphics (Proc. SIGGRAPH) 27, 3, article 98. Google ScholarDigital Library
11. DFG, SFB, 382. Fuel Injection volumetric data set. http://www.volvis.org.Google Scholar
12. Elsinga, G., Oudheusden, B., Scarano, F., and Watt, D. 2004. Assessment and Application of Quantitative Schlieren Methods: Calibrated Color Schlieren and Background Oriented Schlieren. Experiments in Fluids 36, 309–325.Google ScholarCross Ref
13. Faris, G., and Byer, R. 1988. Three-Dimensional Beam-Deflection Optical Tomography of a Supersonic Jet. Applied Optics 27, 24 (Dec.), 5202–5215.Google ScholarCross Ref
14. Fuchs, C., Chen, T., Goesele, M., Theisel, H., and Seidel, H.-P. 2006. Volumetric Density Capture From a Single Image. In Proc. Volume Graphics, 17–22.Google Scholar
15. Goesele, M., Lensch, H., Lang, J., Fuchs, C., and Seidel, H.-P. 2004. DISCO: Acquisition of Translucent Objects. ACM Trans. Graphics (Proc. SIGGRAPH) 23, 3, 835–844. Google ScholarDigital Library
16. Goldhahn, E., and Seume, J. 2007. The Background Oriented Schlieren Technique: Sensitivity, Accuracy, Resolution and Application to a Three-Dimensional Density Field. Experiments in Fluids 43, 2–3, 241–249.Google ScholarCross Ref
17. Grant, I. 1997. Particle Image Velocimetry: a Review. Proceedings of the Institution of Mechanical Engineers 211, 1, 55–76.Google Scholar
18. Gutierrez, D., Seron, F. J., Muñoz, A., and Anson, O. 2006. Simulation of Atmospheric Phenomena. Computers & Graphics 30, 6, 994–1010. Google Scholar
19. Hasinoff, S., and Kutulakos, K. 2007. Photo-Consistent 3D Fire by Flame-Sheet Decomposition. IEEE PAMI 29, 5, 870–885. Google ScholarDigital Library
20. Hawkins, T., Einarsson, P., and Debevec, P. 2005. Acquisition of Time-Varying Participating Media. ACM Trans. Graphics (Proc. SIGGRAPH) 24, 3, 812–815. Google ScholarDigital Library
21. Horn, B., and Schunck, B. 1981. Determining Optical Flow. Artificial Intelligence 17, 185–203.Google ScholarDigital Library
22. Howes, W. L. 1984. Rainbow Schlieren and its Applications. Applied Optics 23, 4, 2449–2460.Google ScholarCross Ref
23. Ihrke, I., and Magnor, M. 2004. Image-Based Tomographic Reconstruction of Flames. Proc. SCA, 367–375. Google Scholar
24. Ihrke, I., Goldluecke, B., and Magnor, M. 2005. Reconstructing the Geometry of Flowing Water. In Proc. ICCV, 1055–1060. Google Scholar
25. Ihrke, I., Ziegler, G., Tevs, A., Theobalt, C., Magnor, M., and Seidel, H.-P. 2007. Eikonal Rendering: Efficient Light Transport in Refractive Objects. ACM Trans. Graphics (Proc. SIGGRAPH) 26, 3, article 59. Google ScholarDigital Library
26. Jensen, H. W., Marschner, S., Levoy, M., and Hanrahan, P. 2001. A Practical Model for Subsurface Light Transport. In Proc. SIGGRAPH, 511–518. Google Scholar
27. Kak, A. C., and Slaney, M. 2001. Principles of Computerized Tomographic Imaging. Society of Industrial and Applied Mathematics. Google Scholar
28. Kindler, K., Goldhahn, E., Leopold, F., and Raffel, M. 2007. Recent Developments in Background Oriented Schlieren Methods for Rotor Blade Tip Vortex Measurements. Experiments in Fluids 43, 2–3, 233–240.Google ScholarCross Ref
29. Kutulakos, K. N., and Steger, E. 2005. A Theory of Refractive and Specular 3D Shape by Light-Path Triangulation. In Proc. ICCV, 1448–1455. Google Scholar
30. Laurentini, A. 1994. The Visual Hull Concept for Silhouette-Based Image Understanding. IEEE PAMI 16, 2 (Feb.), 150–162. Google ScholarDigital Library
31. Lucas, B., and Kanade, T. 1981. An Iterative Image Registration Technique with an Application to Stereo Vision. In Proc. 7th Intl. Joint Conference on Artificial Intelligence, 674–679.Google Scholar
32. Marschner, S., Westin, S., Lafortune, E., Torrance, K., and Greenberg, D. 1999. Image-based BRDF Measurement Including Human Skin. In Proc. EGWR, 131–144. Google Scholar
33. Matusik, W., Pfister, H., Brand, M., and McMillan, L. 2003. A Data-Driven Reflectance Model. ACM Trans. Graphics (Proc. Siggraph) 22, 3, 759–769. Google ScholarDigital Library
34. Meier, G. 2002. Computerized Background-Oriented Schlieren. Experiments in Fluids 33, 181–187.Google ScholarCross Ref
35. Miyazaki, D., and Ikeuchi, K. 2005. Inverse Polarization Raytracing: Estimating Surface Shapes of Transparent Objects. In Proc. CVPR, vol. 2, 910–917. Google Scholar
36. Morris, N. J. W., and Kutulakos, K. N. 2005. Dynamic Refraction Stereo. In Proc. ICCV, 1573–1580. Google Scholar
37. Narasimhan, S., Gupta, M., Donner, C., Ramamoorthi, R., Nayar, S. K., and Jensen, H. W. 2006. Acquiring Scattering Properties of Participating Media by Dilution. ACM Trans. Graphics (Proc. SIGGRAPH) 25, 3, 1003–1012. Google ScholarDigital Library
38. Richard, H., and Raffel, M. 2001. Principle and Applications of the Background Oriented Schlieren (BOS) Method. Measurement Science and Technology 12, 1576–1585.Google ScholarCross Ref
39. Schardin, H. 1942. Die Schlierenverfahren und ihre Anwendungen. Ergebnisse der Exakten Naturwissenschaften 20, 303–439. English translation available as NASA TT F-12731, April 1970 (N70-25586).Google Scholar
40. Scholz, V., Stich, T., Keckeisen, M., Wacker, M., and Magnor, M. 2005. Garment Motion Capture Using Color-Coded Patterns. In Proc. Eurographics, 439–448.Google Scholar
41. Schwarz, A. 1996. Multi-tomographic Flame Analysis with a Schlieren Apparatus. Measurement Science and Technology 7, 406–413.Google ScholarCross Ref
42. Settles, G. S. 2001. Schlieren and Shadowgraph Techniques. Experimental Fluid Mechanics. Springer.Google Scholar
43. Stam, J., and Languénou, E. 1996. Ray-tracing in Non-Constant Media. In Proc. EGSR, 225–234. Google ScholarDigital Library
44. Trifonov, B., Bradley, D., and Heidrich, W. 2006. Tomo-graphic Reconstruction of Transparent Objects. In Proc. EGSR, 51–60. Google Scholar
45. Van Vliet, E., Van Bergen, S., Derksen, J., Portela, L., and Van den Akker, H. 2004. Time-Resolved, 3D, Laser-Induced Fluorescence Measurements of Fine-Structure Passive Scalar Mixing in a Tubular Reactor. Experiments in Fluids 37, 1–21.Google ScholarCross Ref
46. Venkatakrishnan, L., and Meier, E. 2004. Density Measurements using the Background Oriented Schlieren Technique. Experiments in Fluids 37, 237–247.Google ScholarCross Ref
47. Vlasic, D., Baran, I., Matusik, W., and Popović, J. 2008. Articulated Mesh Animation from Multi-view Silhouettes. ACM Trans. Graphics (Proc. SIGGRAPH) 27, 3, article 97. Google ScholarDigital Library
48. Ward, G. 1992. Measuring and Modeling Anisotropic Reflection. In Proc. SIGGRAPH, 265–272. Google Scholar
49. Weickert, J. 1996. Anisotropic Diffusion in Image Processing. PhD thesis, Dept. of Mathematics, University of Kaiserslautern.Google Scholar
50. White, R., Crane, K., and Forsyth, D. 2007. Capturing and Animating Occluded Cloth. ACM Trans. Graphics (Proc. SIGGRAPH) 26, 3, article 34. Google ScholarDigital Library
51. Wilburn, B., Joshi, N., Vaish, V., Levoy, M., and Horowitz, M. 2004. High-Speed Videography Using a Dense Camera Array. In Proc. CVPR, II–294–II–301. Google ScholarDigital Library
52. Zhang, Z. 1999. Flexible Camera Calibration By Viewing a Plane From Unknown Orientations. In Proc. ICCV, 666–673.Google Scholar
