Conference article

Quantification of gaseous structures with volumetric reconstruction from visual hulls

S. Seipel
Faculty of Engineering and Sustainable Technology, University of Gävle, Sweden & Centre of Image Analysis, Uppsala University, Sweden

P. Jenke
Faculty of Engineering and Sustainable Technology, University of Gävle, Sweden

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Published in: Proceedings of SIGRAD 2011. Evaluations of Graphics and Visualization — Efficiency; Usefulness; Accessibility; Usability; November 17-18; 2011; KTH; Stockholm; Sweden

Linköping Electronic Conference Proceedings 65:11, p. 77-82

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Published: 2011-11-21

ISBN: 978-91-7393-008-6

ISSN: 1650-3686 (print), 1650-3740 (online)


3D reconstruction from visual hulls is a well established technique for camera based reconstruction of 3D objects in computer graphics. We propose in this paper to employ visual hull techniques to quantify the volume of diffusely defined gaseous structures. In our evaluation; visual quality of the 3D reconstructions is secondary. Instead; using synthetic ground truth data; we determine the number of independent silhouette images needed to achieve a stable volume estimate. We also estimate the influence of different segmentation results of the silhouette images on final volume estimates. Our results show that comparably few camera views yield to convergent volume estimates. For the type of 3D data studied; visual hull reconstructions overestimate actual volumes with about 50%. This proportion seems to be consistent for different data sets tested and may serve for re-calibration of volume estimation of gaseous structures.


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[Har97] HARTLEY R.: In defense of the eight-point algorithm.IEEE Transactions on Pattern Analysis and Machine Intelligence 19; 6 (1997); 580–593. 2

[hS11] ÅHLÉN J.; SEIPEL S.: Indication of methane gas in irimagery. In Proceedings of IADIS International Conference Computer Graphics; Visualization; Computer Vision and Image Processing 2011 (CGVCVIP 2011) (2011); pp. 187–192. 1

[HZ03] HARTLEY R.; ZISSERMAN A.: Multiple View Geometry in Computer Vision; 2nd ed.; 2nd ed. ed. Cambridge University Press; 2003. 2

[KSK08] KIM H.; SAKAMOTO R.; KITHARA I.; TORIYAMA T.; KOGURE K.: Compensated visual hull with gpu-based optimization. Advances in Multimedia Information Processing ?U PCM 2008 5353 (2008); 573–582. 2; 3

[KT] KIM T.; THÜREY N.: Wavelet turbulence source code. tedkim/WTURB/source.html; visited 10/16/2011. 3

[KTJG08] KIM T.; THÜREY N.; JAMES D.; GROSS M.: Wavelet turbulence for fluid simulation. ACM Trans. Graph. 27 (August 2008); 50:1–50:6. 3

[Lau94] LAURENTINI A.: The visual hull concept for silhouettebased image understanding. IEEE Transactions on Pattern Analysis and Machine Intelligence 16; 2 (1994); 150–162. 2

[Lau95] LAURENTINI A.: How far 3d shapes can be understood from 2d silhouettes. IEEE Transactions on Pattern Analysis and Machine Intelligence 17; 2 (1995); 188–195. 2

[Lau97] LAURENTINI A.: How many 2d silhouettes does it take to reconstruct a 3d object? Computer Vision and Image Understanding 67; 2 (1997); 81–87. 2

[LBN08] LADIKOS A.; BENHIMANE S.; NAVAB N.: Efficient visual hull computation for real-time 3d reconstruction using cuda. In Proceedings of Computer Vision and Pattern Recognition Workshops - CVPRW ’08 (2008); pp. 1–8. 2

[LF95] LUONG Q.-T.; FAUGERAS O.: The fundamental matrix: theory; algorithms; and stability analysis. International Journal of Computer Vision 17 (1995); 43–75. 2

[LMS03] LI M.; MAGNOR M.; SEIDEL H. P.: Improved hardware-accelerated visual hull rendering. Vision; Modeling; and Visualization; Nov. 2003 (2003); 151–158. 2

[LMS04] LI M.; MAGNOR M.; SEIDEL H.: A hybrid hardwareaccelerated algorithm for high quality rendering of visual hulls. In Proceedings of Graphics Interface 2004 (2004); pp. 41–48. 2

[LW10] LIANG C.; WONG K. K.: 3d reconstruction using silhouettes from unordered viewpoints. Image and Vision Computing 28 (2010); 579–589. 2

[SM10] SAFITRI A.; MANNAN M. S.: Methane gas visualization using infrared imaging system and evaluation of temperature dependence of methane gas emissivity. Ind. Eng. Chem. Res. 49; 8 (2010); 3926–3935. 1

[Sze93] SZELISKI R.: Rapid octree construction from image sequences. CVGIP-Image Understanding 58; 1 (1993); 23–32. 2

[Tal07] TALYAN V.: Quantification of methane emission from municipal solid waste disposal in delhi. Resources; Conservation and Recycling 50; 3 (2007); 240–259. 1

[Wue02] WUEBBLES D.: Atmospheric methane and global change. Earth-Science Reviews 57 (2002); 177–210. 1

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