1. Computer Aided Perception Validation of Tone Mapping Operators in the Simulation of Disability Glare A Masters Thesis Proposal by Charles Ehrlich UC Berkeley Department of Architecture

6. Glare Analysis

7. Primary Goal Provide design professionals with a tool to investigate the visual performance of buildings and the environment

8. What About Perception? Existing methods fail to convey an intuitive understanding of the problem of glare.

9. Purpose of Image? Image as design tool To convey veridical information about a proposed building design solution Serve as a communication medium for common understanding for the design team

10. What Makes a Veridical Image? Reproduces the perceptual phenomenon that would otherwise be missing due to the limitations of the display medium.

11. The Fundamental Problem Real world luminances: 10 -4 to 10 5 cd/m 2 (starlight to sunlight) Viewable dynamic range: 1 to 10 4 Typical video displays: 1 to 100 cd/m 2

12. What is in an Image? 4 Bytes per Pixel –RED –GREEN –BLUE –EXPONENT Can store 77 orders of magnitude with 1% accuracy.

13. Radiance linear Algorithm

14. Radiance pcond Algorithm

15. Hypothesis: A rendered image displayed with the appropriate tone mapping algorithm can predict the presence of veiling glare under typical viewing conditions.

16. Literature Search Tumblin. Three Methods of Detail-Preserving ContrastReduction for DisplayedImages. Georgia Institute of Tech. 1999. McNamara. Measures of Lightness Constancy as an index of the perceptual fidelity of computer graphics. EU Conferernce on Visual Perception, 1998. Matkovic. Tone Mapping Techniques and Color Image Difference in Global Illumination, Technical University of Wein. 1997 Pattanaik, P., Ferwerda, S. et.al. A Multiscale Model of Adaptation and Spatial Visionfor Realistic Image Display.Cornell. 1997

17. Matkovic. 1997. Dissertation:Tone Mapping Techniques andColor Image Difference inGlobal Illumination.

19. Pattanaik, P., Ferwerda, S. et. al. A Multiscale Model of Adaptation andSpatial Vision for Realistic ImageDisplay. Cornell. 1997

20. Tumblin Dissertation

23. Mcnamara. 1998. Measures of Lightness Constancy as an index ofthe perceptual fidelity of computergraphics. European Conferernce on Visual Perception.

25. The Validation Method Human subjects are asked to compare: –Scale models of “complex” scenes with and without high dynamic range with –Computer display of rendered equivalents scale model CRT

26. Confounding Factors Scale model versus computer display –Possible to hide the fact that one is a model and one is a computer display Personal sensitivity to glare Color perception anomalies Corrective visual aids

27. Experimental Design Part 1: Comparison –Method of adjustment –Random ordering of trials –Rate the degree of similarity between scale model and displayed image on a 5-point scale Part 2: Glare –View scale model of historical glare study –Rate perception of glare on a 5-point scale

28. Sample Size 20 volunteers if no funding 200 paid subjects, double-blind if funded

29. Analysis of Results Scale Models – Ratings of Similarity Glare –Similarity of Glare Ratings to historical data Average Scene Brightness Rated Brightness Error in Perception

30. The Solution At Hand 3D Visual WYSIWYG Advance warning of potential problems –Too little light –Too much light –Disability Glare –Undesirable lighting quality

31. Veiling Glare

32. Future Research Low light level conditions –Loss of contrast sensitivity –Loss of color acquity –Loss of visual acquity

33. Loss of Contrast Sensitivity

34. The Solution in Context Building Owners, Architects, Lighting Engineers Margin of Safety = over-lighted = waste Inappropriate use of Daylighting

35. Computer Aided Perception System Proposed Design 3D Digital Representation Simulation System Display medium (CRT, paper, etc) Design Team A Situation to be Analyzed or Resolved