research-article

Perception-Based Fast Rendering and Antialiasing of Walkthrough Sequences

Authors:

Karol Myszkowski,

Przemyslaw Rokita,

Takehiro TawaraAuthors Info & Claims

IEEE Transactions on Visualization and Computer Graphics, Volume 6, Issue 4

Pages 360 - 379

https://doi.org/10.1109/2945.895880

Published: 01 October 2000 Publication History

Abstract

In this paper, we consider accelerated rendering of high quality walkthrough animation sequences along predefined paths. To improve rendering performance, we use a combination of a hybrid ray tracing and Image-Based Rendering (IBR) technique and a novel perception-based antialiasing technique. In our rendering solution, we derive as many pixels as possible using inexpensive IBR techniques without affecting the animation quality. A perception-based spatiotemporal Animation Quality Metric (AQM) is used to automatically guide such a hybrid rendering. The Image Flow (IF) obtained as a byproduct of the IBR computation is an integral part of the AQM. The final animation quality is enhanced by an efficient spatiotemporal antialiasing which utilizes the IF to perform a motion-compensated filtering. The filter parameters have been tuned using the AQM predictions of animation quality as perceived by the human observer. These parameters adapt locally to the visual pattern velocity.

References

[1]

http://www.mpi-sb.mpg.de/resources/aqm/, the Web page accompanying to this paper.

[2]

S.J. Adelson and L.F. Hodges, “Generating Exact Ray-Traced Animation Frames by Reprojection,” IEEE Computer Graphics and Applications, vol. 15, no. 3, pp. 43-52, 1995.

Digital Library

[3]

S. Badt Jr., “Two Algorithms for Taking Advantage of Temporal Coherence in Ray Tracing,” The Visual Computer, vol. 4, no. 3, pp. 123-132, 1988.

[4]

B. Girod, “The Information Theoretical Significance of Spatial and Temporal Masking in Video Signals,” Proc. SPIE, vol. 1, 077, pp. 178-187, 1989.

[5]

S.E. Chen, “Quicktime VR—An Image-Based Approach to Virtual Environment Navigation,” SIGGRAPH '95 Proc., pp. 29-38, 1995.

Digital Library

[6]

S. Daly, “The Visible Differences Predictor: An Algorithm for the Assessment of Image Fidelity,” Digital Image and Human Vision, A.B. Watson, ed., pp. 179-206, MIT Press, 1993.

Digital Library

[7]

S. Daly, “Engineering Observations from Spatiovelocity and Spatiotemporal Visual Models,” Human Vision and Electronic Imaging III, vol. 3, 299, pp. 180-191, SPIE, 1998.

[8]

S. Daly, personal communication, 1999.

[9]

L. Darsa B.C. Silva and A. Varshney, “Navigating Static Environments Using Image-Space Simplification and Morphing,” Proc. 1997 Symp. Interactive 3D Graphics, pp. 25-34, 1997.

Digital Library

[10]

R.L. De Valois and K.K. De Valois, Spatial Vision. Oxford Univ. Press, 1990.

[11]

C.J. van den Branden Lambrecht, “Perceptual Models and Architectures for Video Coding Applications,” PhD thesis, Ecole Polytechnique Federale de Lausanne, 1996.

[12]

M.P. Eckert and G. Buchsbaum, “The Significance of Eye Movements and Image Acceleration for Coding Television Image Sequences,” Digital Image and Human Vision, A.B. Watson, ed., pp. 89-98, Cambridge, Mass.: MIT Press, 1993.

Digital Library

[13]

R. Eriksson B. Andren and K. Brunnstrom, “Modelling of Perception of Digital Images: A Performance Study,” Human Vision and Electronic Imaging III, pp. 88-97, SPIE, 1998.

[14]

J.A. Ferwerda S. Pattanaik P. Shirley and D.P. Greenberg, “A Model of Visual Masking for Computer Graphics,” ACM SIGGRAPH '97 Conf. Proc., pp. 143-152, 1997.

Digital Library

[15]

B.K. Guenter H.C. Yun and R.M. Mersereau, “Motion Compensated Compression of Computer Animation Frames,” SIGGRAPH '93 Proc., vol. 27, pp. 297-304, 1993.

Digital Library

[16]

P.J. Hearty, “Achieving and Confirming Optimum Image Quality,” Digital Image and Human Vision, A.B. Watson, ed., pp. 149-162, MIT Press, 1993.

Digital Library

[17]

R. Jain R. Kasturi and B.G. Schunck, Machine Vision. New York: McGraw-Hill, 1995.

Digital Library

[18]

D.H. Kelly, “Motion and Vision 2. Stabilized Spatio-Temporal Threshold Surface,” J. Optical Soc. Am., vol. 69, no. 10, pp. 1,340-1,349, 1979.

[19]

D.H. Kelly, “Spatiotemporal Variation of Chromatic and Achromatic Contrast Thresholds,” J. Optical Soc. Am., vol. 73, no. 6, pp. 742-750, 1983.

[20]

G.E. Legge and J.M. Foley, “Contrast Masking in Human Vision,” J. Optical Soc. Am., vol. 70, no. 12, pp. 1,458-1,471, 1980.

[21]

D. Lischinski and A. Rappoport, “Image-Based Rendering for Non-Diffuse Synthetic Scenes,” Rendering Techniques '98 (Proc. Eurographics Rendering Workshop '98), pp. 301-314, 1998.

[22]

J. Lubin, “A Human Vision Model for Objective Picture Quality Measurements,” Conf. Publication No. 447, pp. 498-503, IEE Int'l Broadcasting Convention, 1997.

[23]

J. Malik and P. Perona, “Preattentive Texture Discrimination with Early Vision Mechanisms,” J. Optical Soc. Am., vol. 7, no. 5, pp. 923-932, 1990.

[24]

W.R. Mark L. McMillan and G. Bishop, “Post-Rendering 3D Warping,” Proc. 1997 Symp. Interactive 3D Graphics, pp. 7-16, 1997.

Digital Library

[25]

L. McMillan, “An Image-Based Approach to 3D Computer Graphics,” PhD thesis, Univ. of North Carolina, Chapel Hill, 1997.

Digital Library

[26]

G. Miller S. Rubin and D. Poncelen, “Lazy Decompression of Surface Light Fields for Precomputed Global Illumination,” Rendering Techniques '98 (Proc. Eurographics Rendering Workshop '98), pp. 281-292, 1998.

[27]

K. Myszkowski P. Rokita and T. Tawara, “Perceptually-Informed Accelerated Rendering of High quality Walkthrough Sequences,” Rendering Techniques '99 (Proc. 10th Eurographics Workshop Rendering), pp. 13-26, 1999.

Digital Library

[28]

J. Nimeroff J. Dorsey and H. Rushmeier, “Implementation and Analysis of an Image-Based Global Illumination Framework for Animated Environments,” IEEE Trans. Visualization and Computer Graphics, vol. 2, no. 4, pp. 283-298, Dec. 1996.

Digital Library

[29]

W. Osberger A.J. Maeder and N. Bergmann, “A Perceptually Based Quantization Technique for MPEG Encoding,” Human Vision and Electronic Imaging III, pp. 148-159, SPIE, 1998.

[30]

J.G. Robson, “Spatial and Temporal Contrast Sensitivity Functions of the Visual System,” J. Optical Soc. Am., vol. 56, pp. 583-601, 1966.

[31]

J. Rovamo V. Virsu and R. Nasaren, “Cortical Magnification Factor Predicts the Photopic Contrast Senstivity of Peripherial Vision,” Nature, vol. 271, pp. 54-56, 1978.

[32]

J.W. Shade S.J. Gortler L. He and R. Szeliski, “Layered Depth Images,” SIGGRAPH 98 Conference Proc., pp. 231-242, 1998.

Digital Library

[33]

M. Shinya, “Spatial Anti-Aliasing for Animation Sequences with Spatio-Temporal Filtering,” SIGGRAPH '93 Proc., vol. 27, pp. 289-296, 1993.

Digital Library

[34]

A. Murat Tekalp, Digital Video Processing. Prentice Hall, 1995.

Digital Library

[35]

P.C. Teo and D.J. Heeger, “Perceptual Image Distortion,” Proc. SPIE, vol. 2, 179, pp. 127-141, 1994.

[36]

X. Tong D. Heeger C. van den Branden Lambrecht, “Video Quality Evaluation Using ST-CIELAB,” Human Vision and Electronic Imaging IV, pp. 185-196, SPIE, 1999.

[37]

B.A. Wandell, Foundations of Vision, Sunderland, Mass.: Sinauer Associates, 1995.

[38]

A.B. Watson, “Temporal Sensitivity,” Handbook of Perception and Human Performance, chapter 6, New York: John Wiley, 1986.

[39]

A.B. Watson, “Toward a Perceptual Video Quality Metric,” Human Vision and Electronic Imaging III, pp. 139-147, SPIE, 1998.

[40]

A.B. Watson and A.J. Ahumada, “Model of Human Visual-Motion Sensing,” J. Optical Soc. Am., vol. 2, no. 2, pp. 322-342, 1985.

[41]

A.B. Watson J. Hu J.F. McGowan III and J.B. Mulligan, “Design and Performance of a Digital Video Quality Metric,” Human Vision and Electronic Imaging IV, pp. 168-174, SPIE, 1999.

[42]

H. Weghorst G. Hooper and D.P. Greenberg, “Improved Computational Methods for Ray Tracing,” ACM Trans. Graphics, vol. 3, no. 1, pp. 52-69, Jan. 1984.

Digital Library

[43]

J.H.D.M. Westerink and C. Teunissen, “Perceived Sharpness in Moving Images,” Proc. SPIE, vol. 1, 249, pp. 78-87, 1990.

[44]

S. Winkler, “A Perceptual Distortion Metric for Digital Color Video,” Human Vision and Electronic Imaging IV, pp. 175-184, SPIE, 1999.

[45]

E.M. Yeh A.C. Kokaram and N.G. Kingsbury, “A Perceptual Distortion Measure for Edge-Like Artifacts in Image Sequences,” Human Vision and Electronic Imaging III, pp. 160-172, SPIE, 1998.

[46]

E. Zeghers K. Bouatouch E. Maisel and C. Bouville, “Faster Image Rendering in Animation through Motion Compensated Interpolation,” Graphics, Design, and Visualization, pp. 49-62, 1993.

Digital Library

Cited By

Whittle JJones MLaramee RTam GVidal F(2018)A deep learning approach to no-reference image quality assessment for Monte Carlo rendered imagesProceedings of the Conference on Computer Graphics & Visual Computing10.2312/cgvc.20181204(23-31)Online publication date: 13-Sep-2018
https://dl.acm.org/doi/10.2312/cgvc.20181204
(2015)Exploiting entropy masking in perceptual graphic renderingImage Communication10.1016/j.image.2015.02.00133:C(1-13)Online publication date: 1-Apr-2015
https://dl.acm.org/doi/10.1016/j.image.2015.02.001
Aydin TČadík MMyszkowski KSeidel H(2010)Video quality assessment for computer graphics applicationsACM Transactions on Graphics10.1145/1882261.186618729:6(1-12)Online publication date: 15-Dec-2010
https://dl.acm.org/doi/10.1145/1882261.1866187
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Index Terms

Perception-Based Fast Rendering and Antialiasing of Walkthrough Sequences
1. Computing methodologies
  1. Computer graphics

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cover image IEEE Transactions on Visualization and Computer Graphics

IEEE Transactions on Visualization and Computer Graphics Volume 6, Issue 4

October 2000

99 pages

ISSN:1077-2626

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Copyright © Copyright © 2000 IEEE. All Rights Reserved.

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IEEE Educational Activities Department

United States

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Published: 01 October 2000

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Cited By

Whittle JJones MLaramee RTam GVidal F(2018)A deep learning approach to no-reference image quality assessment for Monte Carlo rendered imagesProceedings of the Conference on Computer Graphics & Visual Computing10.2312/cgvc.20181204(23-31)Online publication date: 13-Sep-2018
https://dl.acm.org/doi/10.2312/cgvc.20181204
(2015)Exploiting entropy masking in perceptual graphic renderingImage Communication10.1016/j.image.2015.02.00133:C(1-13)Online publication date: 1-Apr-2015
https://dl.acm.org/doi/10.1016/j.image.2015.02.001
Aydin TČadík MMyszkowski KSeidel H(2010)Video quality assessment for computer graphics applicationsACM Transactions on Graphics10.1145/1882261.186618729:6(1-12)Online publication date: 15-Dec-2010
https://dl.acm.org/doi/10.1145/1882261.1866187
Aydin TČadík MMyszkowski KSeidel HDrettakis G(2010)Video quality assessment for computer graphics applicationsACM SIGGRAPH Asia 2010 papers10.1145/1866158.1866187(1-12)Online publication date: 15-Dec-2010
https://dl.acm.org/doi/10.1145/1866158.1866187
Iourcha KYang JPomianowski ALuebke DSlusallek P(2009)A directionally adaptive edge anti-aliasing filterProceedings of the Conference on High Performance Graphics 200910.1145/1572769.1572789(127-133)Online publication date: 1-Aug-2009
https://dl.acm.org/doi/10.1145/1572769.1572789
Boyer VSobczyk D(2006)A model to blend renderingsMachine Graphics & Vision International Journal10.5555/1375858.137586515:3(297-304)Online publication date: 1-Jan-2006
https://dl.acm.org/doi/10.5555/1375858.1375865
Walter BArbree ABala KGreenberg DFinnegan JDorsey J(2006)Multidimensional lightcutsACM SIGGRAPH 2006 Papers10.1145/1179352.1141997(1081-1088)Online publication date: 30-Jul-2006
https://dl.acm.org/doi/10.1145/1179352.1141997
Walter BArbree ABala KGreenberg D(2006)Multidimensional lightcutsACM Transactions on Graphics10.1145/1141911.114199725:3(1081-1088)Online publication date: 1-Jul-2006
https://dl.acm.org/doi/10.1145/1141911.1141997
Longhurst PDebattista KChalmers ANunez DBangay SGain JStraßer W(2006)A GPU based saliency map for high-fidelity selective renderingProceedings of the 4th international conference on Computer graphics, virtual reality, visualisation and interaction in Africa10.1145/1108590.1108595(21-29)Online publication date: 25-Jan-2006
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Stokes WFerwerda JWalter BGreenberg D(2004)Perceptual illumination componentsACM SIGGRAPH 2004 Papers10.1145/1186562.1015795(742-749)Online publication date: 8-Aug-2004
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