Real-time Image Based Lighting with Streaming HDR-light Probe Sequences

Saghi Hajisharif
Linköping University, Sweden

Joel Kronander
Linköping University, Sweden

Ehsan Miandji
Linköping University, Sweden

Jonas Unger
Linköping University, Sweden

Ladda ner artikel

Ingår i: Proceedings of SIGRAD 2012; Interactive Visual Analysis of Data; November 29-30; 2012; Växjö; Sweden

Linköping Electronic Conference Proceedings 81:7, s. 49-58

Visa mer +

Publicerad: 2012-11-20

ISBN: 978-91-7519-723-4

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


We present a framework for shading of virtual objects using high dynamic range (HDR) light probe sequences in real-time. Such images (light probes) are captured using a high resolution HDR camera. In each frame of the HDR video; an optimized CUDA kernel is used to project incident lighting into spherical harmonics in real time. Transfer coefficients are calculated in an offline process. Using precomputed radiance transfer the radiance calculation reduces to a low order dot product between lighting and transfer coefficients. We exploit temporal coherence between frames to further smooth lighting variation over time. Our results show that the framework can achieve the effects of consistent illumination in real-time with flexibility to respond to dynamic changes in the real environment.


I.3.3 [Computer Graphics]: Picture/Image Generation—Image based lighting; pre-computed radiance transfer; high dynamic range video


[AA04] AGGARWAL M.; AHUJA N.: Split aperture imaging for high dynamic range. International Journal of Computer Vision 58; 1 (2004); 7–17. 50

[AB91] ADELSON E. H.; BERGEN J. R.: Computational Models of Visual Processing. MIT Press; Cambridge; Mass.; 1991; ch. 1. The Plenoptic Function and the Elements of Early Vision. 50

[Deb98] DEBEVEC P.: Rendering synthetic objects into real scenes: bridging traditional and image-based graphics with global illumination and high dynamic range photography. In Proceedings of the 25th annual conference on Computer graphics and interactive techniques (New York; NY; USA; 1998); SIGGRAPH ’98; ACM; pp. 189–198. 49; 50

[DM97] DEBEVEC P. E.; MALIK J.: Recovering high dynamic range radiance maps from photographs. In SIGGRAPH 97 (August 1997); pp. 369–378. 50

[GDH06] GHOSH A.; DOUCET A.; HEIDRICH W.: Sequential sampling for dynamic environment maps. In ACM SIGGRAPH 2006 Sketches (New York; NY; USA; 2006); SIGGRAPH ’06; ACM. 51

[Gre03] GREEN R.: Spherical harmonic lighting: The gritty details. Sony Computer Entertainment America (2003). 52

[HH79] HEWITT E.; HEWITT R. E.: The gibbs- wilbraham phe- nomenon: An episode in fourier analysis. Arch. Hist. Exact Sci. 21 (1979); 129–160. 53

[Kaj86] KAJIYA J.: The rendering equation. In SIGGRAPH 86 (1986); pp. 143–150. 50

[KSS02] KAUTZ J.; SLOAN P.-P.; SNYDER J.: Fast; arbitrary brdf shading for low-frequency lighting using spherical harmonics. In EGRW ’02: Proceedings of the 13th Eurographics workshop on Rendering (Aire-la-Ville; Switzerland; Switzerland; 2002); Eurographics Association; pp. 291–296. 50

[KUG12] KRONANDER J.; UNGER J.; GUSTAVSON S.: Realtime hdr video reconstruction for multi-sensor systems. Siggraph 2012 Posters (August 2012). 50

[MH07] MCGUIRE M.; HUGHES J. F.: Optical Splitting Trees for High-Precision Monocular Imaging. IEEE Computer Graphics And Applications 27; April (2007); 32–42. 50

[NM00] NAYAR S.; MITSUNAGA T.: High dynamic range imaging: Spatially varying pixel exposures. In Proc. of CVPR (2000); pp. 472 – 479. 50

[NN05] NARASIMHAN S. G.; NAYAR S. K.: Enhancing Resolution Along Multiple Imaging Dimensions Using Assorted Pixels. IEEE Transactions on Pattern Analysis and Machine Intelligence 27; 4 (2005); 518–530. 50

[NVI11] NVIDIA CORPORATION: NVIDIA CUDA C programming guide; 2011. Version 4.2. 53

[Ram05] RAMAMOORTHI R.: Modeling illumination variation with spherical harmonics. In In Face Processing: Advanced Modeling and Methods (2005); Academic Press. 52

[Ram09] RAMAMOORTHI R.: Precomputation-based rendering. Found. Trends. Comput. Graph. Vis. 3; 4 (Apr. 2009); 281–369. 49; 50

[RH01] RAMAMOORTHI R.; HANRAHAN P.: An efficient representation for irradiance environment maps. In SIGGRAPH ’01: Proceedings of the 28th annual conference on Computer graphics and interactive techniques (New York; NY; USA; 2001); ACM; pp. 497–500. 50

[RH04] RAMAMOORTHI R.; HANRAHAN P.: A signalprocessing framework for reflection. ACM Trans. Graph. 23; 4 (Oct. 2004); 1004–1042. 52

[RWPD06] REINHARD E.; WARD G.; PATTANAIK S.; DEBEVEC P.: High Dynamic Range Imaging – Acquisition; Display and Image-Based Lighting. Morgan Kaufmann; San Francisco; CA; 2006. 50

[SKS02] SLOAN P.-P.; KAUTZ J.; SNYDER J.: Precomputed radiance transfer for real-time rendering in dynamic; lowfrequency lighting environments. In SIGGRAPH ’02: Proceedings of the 29th annual conference on Computer graphics and interactive techniques (New York; NY; USA; 2002); ACM; pp. 527–536. 50; 51

[Slo08] SLOAN. P.-P.: Stupid spherical harmonics (sh). Microsoft Corporation. (2008). 53

[SLS05] SLOAN P.-P.; LUNA B.; SNYDER J.: Local; deformable precomputed radiance transfer. In SIGGRAPH ’05: ACM SIGGRAPH 2005 Papers (New York; NY; USA; 2005); ACM; pp. 1216–1224. 50; 51

[TKTS11] TOCCI M. D.; KISER C.; TOCCI N.; SEN P.: A versatile hdr video production system. ACM Trans. Graph. 30; 4 (July 2011); 41:1–41:10. 50

[UG07] UNGER J.; GUSTAVSON S.: High-dynamic-range video for photometric measurement of illumination. In Proceedings of Sensors; Cameras and Systems for Scientific/Industrial Applications X; IS&T/SPIE 19th International Symposium on Electronic Imaging (Feb 2007); vol. 6501. 50

[WRA05] WANG H.; RASKAR R.; AHUJA N.: High dynamic range video using split aperture camera. In Proc. of OMNIVIS (2005). 50

[YMIN10] YASUMA F.; MITSUNAGA T.; ISO D.; NAYAR S. K.: Generalized Assorted Pixel Camera : Postcapture Control of Resolution ; Dynamic Range ; and Spectrum. IEEE Transactions on Image Processing 19; 9 (2010); 2241–2253. 50

Citeringar i Crossref