Distance Perception in Real and Virtual Environments

1
Distance Perception in Real and Virtual
Environments

• Jodie M. Plumert
• Department of Psychology
• Joseph K. Kearney
• James F. Cremer
• Department Of Computer Science
• University of Iowa

2
Virtual Environments as Laboratories for Studying
Behavior

• Gaining widespread acceptance
• Driving (Uc, Rizzo, Shi, Anderson, and Dawson,
  2004
• Lee, McGehee, Brown, Reyes,
  in press)
• Bicycling (Plumert, Kearney, Cremer, 2004)
• Navigating (Murray, Bowers, West, Pettifer,
  Gibson, 2000
• Warren, Tarr, Kaebling, NEVLab
• Bowman, Davis, Badre, Hodges,
  1999)
• Advantages
• Near natural
• Highly controlled
• Safe
• Issues
• Are virtual environments real enough?
• How well do people perceive distance in VE?

3
Gap Acceptance in the Hank Bicycle Simulator
4
Perceiving Distance in the Real World

• How well do people perceive absolute distance
  from self? (egocentric distance)
• Visually guided judgments
• Matching depth/frontal intervals
• (Gilinsky, 1951, Harway, 1963, Loomis et al.,
  1992)
• People typically underestimate distance
• Visually directed action
• Walking to target with eyes closed
• (Loomis et al., 1992, Philbeck Loomis,
  1997, Rieser et al., 1990)
• People quite accurate up to 20 m.
• People tend to underestimate beyond 20 m.

5
Perceiving Distance in Virtual Worlds

• Distance perception with HMDs
• Triangulation (Loomis Knapp, 2003)
• People view a target, turn and walk a short
  distance, then point back at target.
• Pointing errors indicated that people undershot
  distances.
• Blindfolded walking (Whitmer Sadowski, 1998)
• Compared blindfolded walking in a real hallway
  with blindfolded walking on a treadmill in a
  virtual hallway.
• Mean error similar, but unsigned relative error
  greater in virtual than real environment.
• People made greater errors in both environments
  when they experienced the virtual environment
  first.
• Distance perception with large screen immersive
  display systems (LSIDs)?

6
General Methods

• Real Environment
• Standard university building
• Targets were real people
• Virtual Environment
• Model of real environment
• Targets were billboard people

7
Virtual Environment

• Three 10X8 ft screens
• Rear projection
• Electrohome DLV projectors -1280x1024
  pixels/screen
• Square (Cave-like) configuration
• SGI Onyx with Infinite Reality Graphics

8
Experiment 1

• Subjects 24 undergraduates
• Procedure
• Baseline walking
• Timed normal walking to derive estimate of
  walking speed
• Distance estimates
• Presented 6 randomly ordered distances (20, 40,
  60, 80, 100, and 120 ft) in each environment
  (order counterbalanced)
• Subjects estimated how long it would take to walk
  to the target by starting and stopping a
  stopwatch (without looking at the stopwatch)
• Measures
• Actual time to walk
• Calculated expected time to walk each distance
  from baseline walking speed
• Estimated time to walk
• Elapsed time on a stop watch

9
Results

• Two primary questions
• How closely did time-to-walk estimates correspond
  in real and virtual environments?
• How closely did time estimates in the real and
  virtual environments correspond to actual times?

10
Mean time-to-walk estimates Real environment
first
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Mean time-to-walk estimates Virtual environment
first
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Summary of Experiment 1

• Time-to-walk estimates were remarkably similar
  across the real and virtual environments
• Estimates were accurate up to 40-60 ft
• Time-to-walk estimates more distorted in both
  environments when people experienced the virtual
  environment first

13
Experiment 2 Sighted vs. blindfolded
time-to-walk estimates

• Rationale
• Replicate findings from Experiment 1
• Determine whether time-to-walk estimates differ
  with and without vision
• Subjects
• 16 undergraduates
• Procedure
• Baseline walking
• Sighted judgments same as Experiment 1
• Blindfolded judgments
• People viewed target for 5 s, put on blindfold,
  and started stopwatch when they imagined starting
  to walk

14
Mean sighted time-to-walk estimates
15
Mean blindfolded time-to-walk estimates
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Summary of Experiment 2

• Again, time-to-walk estimates in the real and
  virtual environment were very similar
• Estimates accurate up to about 60 ft
• Time-to-walk estimates very similar with and
  without vision

17
Conclusions

• Time-to-walk estimates are
• Highly similar in real and virtual environments
• Accurate for distances of 20-60 ft
• Underestimated for distances beyond 60 ft

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Why the Difference?

• The Environment
• Time-to-walk measure

19
Why the Difference?

• The Environment
• Large Screen Immersive Display
• Large vertical field of view
• Wu , Ooi, He (2004) Show restricted VFOV
  lead to underestimation of distance
• Whitmer Sadowski (1998) suggest reduced
  VFOV in HMDs degrades cues to distance
• - Knapp Loomis (in press) Limited FOV of
  HMD displays is not the cause of distance
  underestimation in VE
• - Creem-Regehr, Willemsen, Gooch, Thompson
  (2003) Show restricted FOV does lead to
  compression if head motions allowed
• Helmet Weight
• Willemsen, Colton, Creem-Regehr, Thompson
  (2004)

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Why the Difference?

• Time-to-walk measure
• Differs from triangulation and blindfolded
  walking in that it involves imagined rather than
  real movement
• New experiment to compare time-to-walk estimates
  with blindfolded walking
• Preliminary results show similar patterns of
  error
• Blindfolded walking 83 of real
• Imagined walking 73 of real
• Significantly different only at 20 ft

21
Acknowledgments

• NSF Support INT-9724746, EIA-0130864, and
  IIS-0002535
• Students and staff for helping with this
  research
• David Schwebel Pete Willemsen
• Penney Nichols-Whitehead HongLing Wang
• Jennifer Lee Steffan Munteanu
• Sarah Rains Joan Severson
• Sara Koschmeder Tom Drewes
• Ben Fraga Forrest Meggers
• Kim Schroeder Paul Debbins
• Stephanie Dawes Bohong Zhang
• Lloyd Frei Zhi-hong Wang
• Keith Miller
  Xiao-Qian Jiang
• Geb Thomas