“Supra-threshold control of peripheral LOD” by Watson, Walker and Hodges
Conference:
Type(s):
Title:
- Supra-threshold control of peripheral LOD
Presenter(s)/Author(s):
Abstract:
Level of detail (LOD) is widely used to control visual feedback in interactive applications. LOD control is typically based on perception at threshold — the conditions in which a stimulus first becomes perceivable. Yet most LOD manipulations are quite perceivable and occur well above threshold. Moreover, research shows that supra-threshold perception differs drastically from perception at threshold. In that case, should supra-threshold LOD control also differ from LOD control at threshold?In two experiments, we examine supra-threshold LOD control in the visual periphery and find that indeed, it should differ drastically from LOD control at threshold. Specifically, we find that LOD must support a task-dependent level of reliable perceptibility. Above that level, perceptibility of LOD control manipulations should be minimized, and detail contrast is a better predictor of perceptibility than detail size. Below that level, perceptibility must be maximized, and LOD should be improved as eccentricity rises or contrast drops. This directly contradicts prevailing threshold-based LOD control schemes, and strongly suggests a reexamination of LOD control for foveal display.
References:
1. ANSTIS, S. 1986. Motion Perception in the Frontal Plane. Boff, K., Kaufmann, L. & Thomas, J. (eds.), Handbook of Human Perception & Performance, I, John Wiley & Sons., 16-1–16-27.Google Scholar
2. BARRETTE, R. E. 1986. Flight Simulator Visual systems – an Overview. Proc. Soc. Automotive Eng. Conf. Aerospc. Behav. Eng. Tech., 193–198.Google ScholarCross Ref
3. BLAKEMORE, C., MUNCEY, J. P. J. & RIDLEY, R. M. 1973. Stimulus Specificity in the Human Visual System. Vision Rsrch., 13, 1915–1931.Google ScholarCross Ref
4. BOLIN, M. & MEYER, G. 1998. A Perceptually Based Adaptive Sampling Algorithm. Proc. ACM SIGGRAPH, 299–309. Google ScholarDigital Library
5. BONNEH, Y. & SAGI, D. 1998. Effects of Spatial Configuration on Contrast Detection. Vision Rsrch., 38, 3541–3553.Google ScholarCross Ref
6. BONNEH, Y. & SAGI, D. 1999. Contrast Integration Across Space. Vision Rsrch., 39, 2597–2602.Google ScholarCross Ref
7. CANNON, M. W. 1985. Perceived Contrast in the Fovea and Periphery. J. Optical Soc. Am. A, 2, 10, 1760–1768.Google ScholarCross Ref
8. CARRASCO, M. & FRIEDER, K. 1997. Cortical Magnification Neutralizes the Eccentricity Effect in Visual Search. Vision Rsrch., 37, 63–82.Google ScholarCross Ref
9. CHANDLER, D. M. & HEMAMI, S. S. 2002. Additivity Models for Suprathreshold Distortion Quantized Wavelet-Coded Images. Proc. SPIE Human Vision & Electronic Imaging, 4662, 105–118.Google ScholarCross Ref
10. CHANDLER, D. M. & HEMAMI, S. S. 2003. Suprathreshold Image Compression Based on Contrast Allocation and Global Precedence. Proc. SPIE Human Vision & Electronic Imaging, 5007, 73–86.Google ScholarCross Ref
11. VAN DIEPEN, P. M. J., RUELENS, L. & D’YDEWALLE, G. 1999. Brief Foveal Masking During Scene Perception. Acta Psychologica, 101, 91–103.Google ScholarCross Ref
12. VAN DIEPEN, P. M. J. & WAMPERS, M. 1998. Scene Exploration with Fourier-Filtered Peripheral Information. Perception, 27, 1141–1151.Google ScholarCross Ref
13. ELMES, D. G., KANTOWITZ, B. H., & ROEDIGER, H. L. 2003. Research Methods in Psychology, 7th ed. Thomson Wadsworth.Google Scholar
14. FERNIE, A. 1995. Helmet-Mounted Display with Dual Resolution. J. Soc. for Information Display, 3, 4, 151–153.Google ScholarCross Ref
15. FERWERDA, J. A., RUSHMEIER, H. & WATSON, B. A. 2002. Psychometrics 101: How to Design, Conduct, and Analyze Perceptual Experiments in Computer Graphics. ACM SIGGRAPH Course 58 Notes.Google Scholar
16. FREDERICKSEN, R. E. & HESS, R. F. 1997. Temporal Detection in Human Vision: Dependence on Stimulus Energy. J. Optical Soc. Am. A, 14, 2557–2569.Google ScholarCross Ref
17. FREDERICKSEN, R. E. & HESS, R. F. 1999. Temporal Detection in Human Vision: Dependence on Spatial Frequency. J. Optical Soc. Am. A, 16, 2601–2611.Google ScholarCross Ref
18. FUNKHOUSER, T. & SÉÉQUIN, C. 1993. Adaptive Display Algorithm For Interactive Frame Rates During Visualization Of Complex Virtual Environments. Proc. ACM SIGGRAPH, 247–254. Google ScholarDigital Library
19. GEISLER, W. S. & CHOU, K.-L. 1995. Separation of Low-Level and High-Level Factors in Complex Tasks: Visual Search. Psych. Review, 102, 356–378.Google ScholarCross Ref
20. GEORGESON, M. A. & SULLIVAN, G. D. 1975. Contrast Constancy: Deblurring in Human Vision by Spatial Frequency Channels. J. Physiology (London), 252, 627–656.Google ScholarCross Ref
21. GRAHAM, N. 1989. Visual Pattern Analyzers. Oxford University Press.Google Scholar
22. VAN DE GRIND, W. A., KOENDERINK, J. J. & VAN DORN, A. J. 1986. The Distribution of Human Motion Detector Properties in the Monocular Visual Field. Vision Rsrch., 26, 797–810.Google ScholarCross Ref
23. VAN DE GRIND, W. A., KOENDERINK, J. J. & VAN DORN, A. J. 2000. Motion Detection From Photopic to Low Scotopic Luminance Levels. Vision Rsrch., 40, 187–199.Google ScholarCross Ref
24. HOWLETT, E. 1992. High-Resolution Insets in Wide-Angle Head-Mounted Stereoscopic Displays. Proc. SPIE Stereoscopic Displays & Applications, 1669, 193–203.Google Scholar
25. KELLY, D. H. 1979. Motion and Vision. II. Stabilized Spatio-Temporal Threshold Surface. J. Optical Soc. Am., 69, 1340–1349.Google Scholar
26. KELLY, D. H. 1984. Retinal Inhomogeneity. I. Spatiotemporal Contrast Sensitivity. J. Optical Soc. Am. A, 1, 107–113.Google ScholarCross Ref
27. KESSLER, G. D., BOWMAN, D. A. & HODGES, L. F. 2000. The Simple Virtual Environment Library, an Extensible Framework for Building VE Applications. Presence, 9, 2, 189–208. Google ScholarDigital Library
28. KOENDERINK, J. J., BOUMAN, M. A., BUENO DE MESQUITA, A. E. & SLAPPENDEL, S. 1978. Perimetry of Contrast Detection Thresholds of Moving Spatial Sine-Wave Patterns. J. Optical Soc. Am., 68, 845–865.Google ScholarCross Ref
29. KULIKOWSKI, J. J. 1976. Effective Contrast Constancy and Linearity of Contrast Sensation. Vision Rsrch., 16, 1419–1431.Google ScholarCross Ref
30. LIVERSEDGE, S. P. & FINDLAY, J. M. 2000. Saccadic Eye Movements and Cognition. Trends in Cognitive Sciences, 4, 1, 6–14.Google ScholarCross Ref
31. VAN LOON, E. M., HOOGE, I. TH. C. & VAN DEN BERG, A. V. 2003. Different Visual Search Strategies in Stationary and Moving Radial Patterns. Vision Rsrch., 43, 1201–1209.Google ScholarCross Ref
32. LUEBKE, D. & HALLEN, B. 2001. Perceptually Driven Simplification for Interactive Rendering. Proc. Eurographics Rendering Wkshp., 223–234. Google ScholarDigital Library
33. LUEBKE, D., REDDY, M. COHEN, J., VARSHNEY, A., WATSON, B. A. & HUEBNER, R. 2003. Level of Detail for 3D Graphics, Morgan Kaufman. Google ScholarDigital Library
34. MCKEE, S. P. & NAKAYAMA, K. 1984. The Detection of Motion in the Peripheral Visual Field. Vision Rsrch., 24, 25–32.Google ScholarCross Ref
35. MCKEE, S. P., SILVERMAN, G. H. & NAKAYAMA, K. 1986. Precise Velocity Discrimination Despite Random Variations in Temporal Frequency and Contrast. Vision Rsrch., 26, 609–619.Google ScholarCross Ref
36. NAKAYAMA, K. & SILVERMAN, G. H. 1985. Detection and Discrimination of Sinusoidal Grating Displacements. J. Optical Soc. Am. A, 2, 267–274.Google ScholarCross Ref
37. NIEMANN, T. & HOFFMAN, K.-P. 1997. Motion Processing for Saccadic Eye Movements During the Visually Induced Sensation of Ego-Motion in Humans. Vision Rsrch., 37, 3163–3170.Google ScholarCross Ref
38. NOTHDURFT, H.-C. 2002. Attention Shifts to Salient Targets. Vision Rsrch., 42, 1287–1306.Google ScholarCross Ref
39. OHSHIMA, T., YAMAMOTO, H. & TAMURA, H. 1996. Gaze-Directed Adaptive Rendering For Interacting With Virtual Space. Proc. IEEE Virtual Reality Annual International Symp., 103–110. Google ScholarDigital Library
40. PARKHURST, D. J. & NIEBUR, E. 2002. Variable-Resolution Displays: A Theoretical, Practical, and Behavioral Evaluation. Human Factors, 44, 4, 611–629.Google ScholarCross Ref
41. PELI, E., AREND, L. & LABIANCA, A. T. 1996. Contrast Perception Across Changes In Luminance And Spatial Frequency. J. Optical Soc. Am. A, 13, 10, 1953–1959.Google ScholarCross Ref
42. RAMASUBRAMANIAN, M., PATTANAIK, S. N. & GREENBERG, D. P. 1999. A Perceptually Based Physical Error Metric for Realistic Image Synthesis. Proc. ACM SIGGRAPH, 73–82. Google ScholarDigital Library
43. RAYNER, K. 1998. Eye Movements in Reading and Information Processing: 20 Years of Research. Psych. Bulletin, 124, 372–422.Google ScholarCross Ref
44. REDDY, M. 1998. Specification and Evaluation of Level of Detail Selection Criteria. Virtual Reality: Rsrch., Development & Application, 3, 2, 132–143.Google ScholarDigital Library
45. ROYDEN, C. S., WOLFE, W. M. & KLEMPEN, N. 2001. Visual Search Asymmetries in Motion and Optic Flow Fields. Perception & Psychophysics, 63, 436–444.Google ScholarCross Ref
46. SAIDA, S. & IKEDA, M. 1979. Useful Visual Field Size for Pattern Perception. Perception & Psychophysics, 25, 2, 119–125.Google ScholarCross Ref
47. SCHARFF, L. F., HILL, A. L. & AHUMADA, A. J. 2000. Discriminability Measures for Predicting Readability of Text on Textured Backgrounds. Optics Express, 6, 81–91.Google ScholarCross Ref
48. SEKULER, R., WATAMANIUK, S. N. J. & BLAKE, R. 2002. Perception of Visual Motion. In Pashler, H. (series ed.) & Yantis, S. (vol. ed.), Stevens’ Handbook of Experimental Psych.: Vol. 1 Sensation & Perception, 3rd ed. J. Wiley.Google Scholar
49. SHIORI, S. & IKEDA, M. 1989. Useful Resolution for Picture Perception as a Function of Eccentricity. Perception, 18, 347–361.Google ScholarCross Ref
50. SMITH, A. T. & SNOWDEN, R. J. 1994. Visual Detection of Motion. Academic Press.Google Scholar
51. SORKINE, O., COHEN-OR, D. & TOLEDO, S. 2003. High-Pass Quantization For Mesh Encoding. Proc. Eurographics/ACM SIGGRAPH Symp. Geometry Processing, 42–51. Google ScholarDigital Library
52. TREISMAN, A. & GELADE, G. 1980. A Feature-Integration Theory of Attention. Cognitive Psych., 12, 97–136.Google ScholarCross Ref
53. TURANO, K. & PANTLE, A. 1989. On the Mechanism That Encodes the Movement of Contrast Variations: Velocity Discrimination. Vision Rsrch., 29, 207–221.Google Scholar
54. TYNAN, P. & SEKULER, R. 1982. Motion Processing in Peripheral Vision: Reaction Time and Perceived Velocity. Vision Rsrch., 22, 61–68.Google ScholarCross Ref
55. VOLEVICH, V., MYSZKOWSKI, K., KHODULEV, A. & KOPYLOV, E. 2000. Using the Visual Difference Predictor to Improve Performance of Progressive Global Illumination Computation. ACM Trans. Graphics, 19, 2, 122–161. Google ScholarDigital Library
56. WATSON, A. B. & AHUMADA, A. J. 1985. Model of Human Visual-Motion Sensing. J. Optical Soc. Am. A, 2, 322–342.Google ScholarCross Ref
57. WATSON, A. B. & TURANO, K. 1995. The Optimal Motion Stimulus. Vision Rsrch., 35, 325–336.Google ScholarCross Ref
58. WATSON, B. A., WALKER, N. & HODGES, L. F. 1997. Managing Level of Detail Through Head-Tracked Peripheral Degradation: a Model and Resulting Design Principles. Proc. ACM Virtual Reality Software Technology, 59–64. Google ScholarDigital Library
59. WATSON, B. A., WALKER, N., RIBARSKY, W. R. & SPAULDING, V. 1998. The Effects of Variation in System Responsiveness on User Performance in Virtual Environments. Human Factors, 40, 3, 403–414.Google ScholarCross Ref
60. WATSON, B. A., WALKER, N., HODGES, L. F. & WORDEN, A. 1997. Managing Level of Detail Through Peripheral Degradation: Effects on Search Performance with a Head-Mounted Display. ACM Trans. Computer-Human Interaction, 4, 4, 323–346. Google ScholarDigital Library
61. YOSHIDA, A., ROLLAND, J. & REIF, J. 1995. Design and Applications of a High-Resolution Insert Head-Mounted-Display. Proc. Virtual Reality Annual International Symp., 84–93. Google ScholarDigital Library