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TitleThe Influence of Lighting Quality on Presence and Task Performance in Virtual Environments
LanguageEnglish
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Page 1

The Influence of Lighting Quality on Presence and Task

Performance in Virtual Environments




by
Paul Michael Zimmons





A dissertation submitted to the faculty of the University of North Carolina at
Chapel Hill in partial fulfillment of the requirements for the degree of Doctor
of Philosophy in the Department of Computer Science.




Chapel Hill
2004





Approved by:

____________________________________
Advisor: Dr. Frederick P. Brooks, Jr.

____________________________________
Reader: Prof. Mary C. Whitton

____________________________________
Reader: Dr. Abigail T. Panter

____________________________________
Dr. Anselmo A. Lastra

____________________________________
Dr. Joseph B. Hopfinger

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ii












































2004
Paul Michael Zimmons

ALL RIGHTS RESERVED

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in higher accuracy than inconsistent lighting. As the lighting became more

inconsistent between the search object and the table objects, inaccuracies

increased. The search object lighting model had a more noticeable influence

on search accuracy than the table object lighting model. A summary of the

accuracy scores by condition is given in Table 5.2.



Search Object Lighting Model (SOLM)

Global (Gi) Local (Li) Ambient (Ai)

Global (Gt) (1) 80.3% (2) 74.4% (3) 48.6%

Local (Lt) (4) 73.9% (5) 77.3% (6) 62.5%

T
ab

le
O

b
je

ct


Li
gh

ti
n

g
M

od
el


(T

O
LM

)

Ambient (At) (7) 54.5% (8) 66.2% (9) 70.3%



Table 5.2: Accuracy scores for the different conditions in the Knot
Experiment. (n) = condition number.



Significance testing for accuracy was computed using an Arcsin

Transform to account for the changes in the variance of participants’ scores

(Hogg and Craig, 1978).

Consistent vs. Inconsistent. When the accuracy scores of the

consistent lighting conditions (conditions G/G, L/L, and A/A) were compared

to the accuracy scores of the inconsistent lighting conditions (conditions L/G,

A/G, G/L, A/L, G/A, L/A), participants scored significantly higher in the

conditions with consistent lighting, 76% vs. 63% (p < 0.001). Condition G/G

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had the highest accuracy scores of any of the nine conditions at 80%

accuracy.

Conditions G/G, L/L, and A/A, where lighting was consistent, had

accuracy scores of 80%, 77%, and 70% respectively (Figure 5.3). However, this

downward trend in accuracy did not approach significance (p < 0.13).

Conditions G/G and L/L (global and local illumination) grouped together were

close to being significantly more accurate than ambient illumination (79% vs.

70%, p < 0.051).

1 5 9

Condition (1=G/G, 5=L/L, 9=A/A)

0.60

0.65

0.70

0.75

0.80

0.85

0.90

95
%

C
I f

or
P

er
ce

nt
ag

e
C

or
re

ct





Comparing global and local illumination against each other showed no

significant difference in accuracy (p < 0.58). There was a 69% overlap in the

95% confidence intervals between the global and local illumination accuracy

scores. However, the t-test used to compare the scores showed a low power

value (power=0.08, β=0.92). Thus, our ability to determine if local and global

illumination are the same in their ability to achieve high accuracy is limited. If

Figure 5.3: Accuracy scores for global, local, and ambient
consistent lighting conditions.

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Tan, D., D. Gergle, P Scupelli, and R. Pausch (2003). With similar visual
angles, larger displays improve spatial performance. Proceedings of
the Conference on Human Factors in Computing Systems, 217-224.


Tarr, M. J., D. Kersten and H. H. Bulthoff (1998). Why the visual recognition

system might encode the effects of illumination. Vision Research, 38:
2259-2276.


Taylor, L.H. and E. W. Sucov (1974). The movement of people towards lights.

Journal of the Illuminating Engineering Society, 3: 237-241.

Taylor, L. H., E. W. Sucov, and D. H. Shaffer (1973). Display lighting

preferences (extended abstract). Lighting Design and Application, 14.

Thompson, W. B., P. Shirley, B. Smits, D. J. Kersten and C. Madison (1998).

Visual glue. University of Utah Tech Report UUCS-98-007.

Thought Technology, Ltd. (2001). ProComp+ tethered telemetry system.

http://www.thoughttechnology.com.

Tipler, P. (1991). Physics for scientists and engineers, 2nd Ed. New York, New

York, Worth Publishers.

Torrance, K., and E. M. Sparrow (1967). Theory of off-specular reflection

from roughened surfaces. Journal of the Optical Society of America,
57(9): 1105-1114.


Usoh, M., K. Arthur, M. Whitton, R. Bastos, A. Steed, M. Slater, and F.

Brooks (1999). Walking > walking-in-place > flying in virtual
environments. Proceedings of ACM SIGGRAPH 99, 359-364.


Usoh, M., E. Catena, S. Arman and M. Slater (2000). Using presence

questionnaires in reality. Presence: Teleoperators and Virtual
Environments, 9(5): 497-503.


Veitch, J. (2001). Psychological processes influencing lighting quality.

Journal of the Illuminating Engineering Society, 30(1): 124-140.

Wanger, L. (1992). The effect of shadow quality on the perception of spatial

relationships in computer generated imagery. Proceedings of ACM
SIGGRAPH 92, 39-42.


Watson, D., L. A. Clark and A. Tellegen (1988). Development and validation

of brief measures of Positive and Negative Affect: The PANAS scales.
Journal of Personality and Social Psychology, 54: 1063-1070.

Page 264

244


Welch, R. B., T. T. Blackman, A. Liu, B. A. Mellers and L. W. Stark (1996).

The effects of pictorial realism, delay of visual feedback, and observer
interactivity on the subjective sense of presence. Presence:
Teleoperators and Virtual Environments, 5(3): 263-273.


Whitted, T. (1980). An improved illumination model for shaded display.

Communications of the ACM, 23(6): 343-349.

Willemsen, P. and A. Gooch (2002). An experimental comparison of perceived

egocentric distance in real, image-based, and traditional virtual
environments using direct walking tasks. University of Utah Tech Report
UUCS-02-009.


Williams, L. (1994). Recall of childhood trauma: A prospective study of

women's memories of child sexual abuse. Journal of Consulting and
Clinical Psychology, 62, 1167-1176.


Witmer, B.G. and M. J. Singer (1998). Measuring presence in virtual

environments: A presence questionnaire. Presence: Teleoperators in and
Virtual Environments, 7(3): 225-240.


Wooding, D. S. (2002). Fixation maps: Quantifying eye-movement traces.

Proceedings of ACM Eye Tracking Research and Applications
Symposium, 31-36.


Yamaguchi, T. (1999). Physiological studies of human fatigue by a virtual

reality system. Presence: Teleoperators and Virtual Environments, 8(1):
112-124.


Yasuda, T., S. Yokoi, J. Toriwaki, and K. Inagaki (1992). A shading model

for cloth objects. IEEE Computer Graphics and Applications, 12(6): 15-
24.


Yorks, P. and D. Ginthner (1987). Wall lighting placement: Effect on

behavior in the work environment. Lighting Design and Application,
17, 30-37.


Zeltzer, D. (1992). Autonomy, interaction, and presence. Presence:

Teleoperators and Virtual Environments, 1(1): 127-132.

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