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Synthesizing and editing dynamic flames with color temperature

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Generating computer animated flames is a difficult and computationally expensive problem. Dynamic textures provide an effective means for extrapolating and synthesizing dynamic flames, but aggravates color distortion due to the high correlation of RGB components. A novel method for dynamic flame texture synthesis using color temperature is proposed in this paper. Firstly, the color-temperature mapping is calculated by using the Planck’s law and two-color pyrometric technique to avoid color distortion. Secondly, a novel dynamic texture model is presented to transform the RGB space into temperature space. Finally, the dynamic flames editing is presented to support physical temperature adjustment. Experimental results illustrate that our approach is effective to synthesize visually plausible dynamic flames without color distortions and to edit dynamic flames with intuitive physical interpretation.

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  1. 1.

    Wu ZH, Zhou Z, Wu W (2011) Realistic fire simulation: a survey. CAD/Graphics 2011. Jinan, China, pp 333–340

  2. 2.

    Fan WS, Wang B, Paul JC et al (2013) An octree-based proxy for collision detection in large-scale particle systems. Sci China Inf Sci 56:012104

  3. 3.

    Wang CB, Zhang Q, Kong FL (2013) Simulation of free-surface flow using a boundless grid. Sci China Inf Sci 56:032104

  4. 4.

    Yang S, Qi Y, Qin H (2012) A particle-based method for granular flow simulation. Sci China Inf Sci 55:1062–1072

  5. 5.

    Zhu J, Liu YQ, Chang YZ et al (2013) Amimating turbulent water by vortex shedding in PIC/FLIP. Sci China Inf Sci 56:032102

  6. 6.

    Hossain MM, Lu G, Duo S et al (2013) Three-dimensional reconstruction of flame temperature and emissivity distribution using optical tomographic and two-colour pyrometric techniques. Meas Sci Technol 24:74010

  7. 7.

    Wang L, Chen JS, He JP et al (2012) High-speed reconstruction for ultra-low resolution faces. Sci China Inf Sci 55:2102–2108

  8. 8.

    Soatto S, Doretto G, Wu YN (2001) Dynamic textures. In: ICCV 2001, Vancouver, Canada, vol 2, pp 439–446

  9. 9.

    Doretto G, Soatto S (2003) Editable dynamic textures. In: CVPR 2003, Madison, Wisconsin, USA, vol 2, pp 137–142

  10. 10.

    Ghanem BS (2011) Dynamic textures: Models and applications. Dissertation for the Doctoral Degree. University of Illinois at Urbrna-Champaign, 2011, pp 15–38

  11. 11.

    Fan J, Shi XY, Zhou Z et al (2013) An optimized texture-by-numbers synthesis method and its visual applications. Sci China Inf Sci 56:052104

  12. 12.

    Nelson RC, Polana R (1992) Qualitative recognition of motion using temporal texture. CVGIP Image Underst 56:78–89

  13. 13.

    De Bonet JS (1997) Multiresolution sampling procedure for analysis and synthesis of texture images. In: SIGGRAPH 1997, Los Angeles, CA, USA, pp 361–368

  14. 14.

    Fournier A, Reeves WT (1986) A simple model of ocean waves. In: SIGGRAPH 1986, Dallas, USA, vol 20, pp 75–84

  15. 15.

    Stam J, Fiume E (1995) Depiction of fire and other gaseous phenomena using diffusion Processes. In: SIGGRAPH 1995, New York, USA, pp 129–136

  16. 16.

    Foster N, Fediw R (2001) Practical animation of liquids. In: SIGGRAPH 2001, Los Angeles, USA, pp 23–30

  17. 17.

    Bouthemy P, Fablet R (1998) Motion characterization from temporal cooccurrences of local motion-based measures for video indexing. In: ICPR 1998, Queensland, Australia, vol 1, pp 905–908

  18. 18.

    Rahman A, Murshed M (2008) Dynamic texture synthesis using motion distribution statistics. J Res Pract Inf Tech 40:129–148

  19. 19.

    Comaniciu D, Ramesh V, Meer P (2003) Kernel-based object tracking. IEEE Trans Pattern Anal 25:564–577

  20. 20.

    Schödl A, Szeliski R, Salesin DH et al (2000) Video textures. In: SIGGRAPH 2000, New Orleans, Louisiana, USA, pp 489–498

  21. 21.

    Guo Y, Zhao G, Chen J et al (2009) Dynamic texture synthesis using a spatial temporal descriptor. In: ICIP 2009, Cairo, Egypt, pp 2277–2280

  22. 22.

    Kwatra V, Schödl A, Essa I et al (2003) Graphcut textures: image and video synthesis using graph cuts. ACM Trans Graphic 22:277–286

  23. 23.

    Lizarraga-Morales RA, Guo Y, Zhao G et al (2014) Local spatiotemporal features for dynamic texture synthesis. EURASIP J Image Video 1:1–15

  24. 24.

    Doretto G (2005) Modeling dynamic scenes with active appearance. In: CVPR 2005, San Diego, CA, USA, vol 1, 66–73

  25. 25.

    Yuan L, Wen F, Liu C et al (2004) Synthesizing dynamic texture with closed-loop linear dynamic system. In: ECCV 2004. Prague, Czech Republic, pp 603–616

  26. 26.

    Chan AB, Vasconcelos N (2009) Layered dynamic textures. IEEE Trans Pattern Anal 31:1862–1879

  27. 27.

    Yan X, Chang H, Chen X (2013) Temporally multiple dynamic textures synthesis using piecewise linear dynamic systems. In: ICIP 2013, Melbourne, Australia, pp 3167–3171

  28. 28.

    Xu L, Sun H, Jia J et al (2007) Dynamic texture synthesis in the yuv color-space. In: ICEC 2007, Shanghai, China, pp 243–248

  29. 29.

    Costantini R, Sbaiz L, Susstrunk S (2006) Dynamic texture synthesis: Compact models based on luminance-chrominance color representation. In: ICIP 2006, Atlanta, Georgia, USA, pp 2085–2088

  30. 30.

    Abraham B, Camps OI, Sznaier M (2005) Dynamic texture with fourier descriptors. In Texture 2003, Beijing, China pp 53–58

  31. 31.

    Ghanem B, Ahuja N (2007) Phase based modelling of dynamic textures. In: ICCV 2007, Rio de Janeiro, Brazil, pp 1–8

  32. 32.

    Shen J, Jin X, Zhou C et al (2006) Dynamic textures using wavelet analysis. In: Technologies for E-learning and digital entertainment, Hangzhou, China, pp 1070–1073

  33. 33.

    Nikfetrat N, Lee WS (2012) Fire visualization using eigenfires. Intelligent Computer Graphics. Springer, Berlin Heidelberg 2012:189–207

  34. 34.

    Wang L, Ye WF, Duan M (2013) Real-time rendering of flames on arbitrary deformable objects. Sci China Inf Sci 56:082116

  35. 35.

    Siegel R (2002) Thermal radiation heat transfer, 4 edn. Taylor & Francis, New York, pp 3–31

  36. 36.

    Huang Y, Yan Y, Riley G (2000) Vision-based measurement of temperature distribution in a 500-kW model furnace using the two-colour method. Measurement 28:175–183

  37. 37.

    Jiang F, Liu S, Liang S et al (2009) Visual flame monitoring system based on two-color method. Thermal Sci 18:284–288

  38. 38.

    Incropera FP, De Witt DP (2011) Fundamentals of heat and mass transfer, 7th edn. Wiley, New York, pp 801–847

  39. 39.

    Panagiotou T, Levendis Y, Delichatsios M (1996) Measurements of particle flame temperatures using three-color optical pyrometry. Combust Flame 104:272–287

  40. 40.

    Hunt RWG, Pointer MR (2011) Measuring colour, 4th edn. Wiley, Chichester, pp 1–72

  41. 41.

    Hunt R, Pointer MR (1985) A colour-appearance transform for the CIE 1931 standard colorimetric observer. Color Res Appl 10:165–179

  42. 42.

    Walker J Colour rendering of spectra [OL]. [2014-05-15]. http://www.fourmilab.ch/documents/specrend

  43. 43.

    Suo JL, Ji XY, Dai QH (2012) An overview of computational photography. Sci China Inf Sci 55:1229–1248

  44. 44.

    Huang Y, Yan Y (2000) Transient two-dimensional temperature measurement of open flames by dual-spectral image analysis. Trans Inst Meas Control 22:371–384

  45. 45.

    Wang XG, Wu ZH, Zhou Z et al (2013) Temperature field reconstruction of combustion flame based on high dynamic range images. Opt Eng 52:43601

  46. 46.

    Zhao X, Zhong Z, Wei W (2012) Radiance-based color calibration for image-based modeling with multiple cameras. Sci China Inf Sci 55:1509–1519

  47. 47.

    Lu G, Yan Y, Riley G et al (2002) Concurrent measurement of temperature and soot concentration of pulverized coal flames. IEEE Trans Instrum Meas 51:990–995

  48. 48.

    Van Wylen GJ, Sonntag RE, Borgnakke C (1994) Fundamentals of classical thermodynamics, 4th edn. Wiley, New York, pp 714–804

  49. 49.

    Atcheson B, Ihrke I, Bradley D et al (2007) Imaging and 3D tomographic reconstruction of time-varying inhomogeneous refractive index fields. In: SIGGRAPH 2007, San Diego, California, USA, vol 32, pp 1–8

  50. 50.

    Artbeats. ReelFire 2 [OL]. [2014-05-15]. http://www.artbeats.com/collections/214-ReelFire-2

  51. 51.

    Lei T, Wang Y, Fan YY et al (2013) Vector morphological operators in HSV color space. Sci China Inf Sci 56:012303

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This work was supported by the National High Technology Research and Development Program of China (2012AA011803), the National Natural Science Foundation of China (61472020), and the Specialized Research Foundation of China (20121102130004). We sincerely thank Professor Voicu Popescu of Purdue University for his lectures about high-quality graphics paper writing.

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Correspondence to Zhong Zhou.

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Wu, Z., Zhou, Z., Dou, F. et al. Synthesizing and editing dynamic flames with color temperature. Chin. Sci. Bull. 59, 5379–5392 (2014). https://doi.org/10.1007/s11434-014-0672-0

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  • Color temperature
  • Color distortion
  • Two-color pyrometric
  • Dynamic flame editing
  • Dynamic texture
  • Fire/flame