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Perceived collision with an obstacle in a virtual environment. Russell L Woods, Jennifer C Shieh Laurel Bobrow, Avni Vora , James Barabas, Robert B Goldstein and Eli Peli Schepens Eye Research Institute and Harvard Medical School, Boston, MA. ARVO 2003. How do you define a collision?. - PowerPoint PPT Presentation
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Perceived collision with an obstacle in a virtual environment
Russell L Woods, Jennifer C ShiehLaurel Bobrow, Avni Vora, James
Barabas, Robert B Goldstein and Eli Peli
Schepens Eye Research Institute and Harvard Medical School, Boston, MA
ARVO 2003
How do you define a collision?
In the literature: • Center to center• No consideration of the physical size of the
observer or “safe distance”
• Evaluated visual information (e.g. , TTC, heading perception) or cognitive issues (e.g. search)
• Way-finding
• Collision detection from relative motion of obstacle and other objects
• Stick figures, sparse environment• Simulated fixation task• Center to center• Angular perspective
Cutting, Vishton & Braren (1995)
Are potential-collision decisions based on physical size?
(i.e. how big you are)
The task
•Walk on a treadmill (self propelled)•Rear projected screen (77 cm, 95 degrees wide)•“infinite” shopping mall corridor
•Obstacle appeared at 5m or 15m for 1 second
•Square pillars with images of people (30cm or 70cm wide)
•Task: Would you have collided with the obstacle?•New path before each obstacle•Random angular offsets of paths
Closest distance to obstacle
Some obstacles crossed the path
Obstacle appearance distance
The task
•Walk on a treadmill (self propelled)•Rear projected screen (77 cm, 85 degrees wide)•“infinite” shopping mall corridor
•Obstacle appeared at 5m or 15m for 1 second
•Square pillars with images of people (30cm or 70cm wide)
•Task: Would you have collided with the obstacle?•New path before each obstacle•Random angular offsets of paths
small obstacle, 5m, 55cm
large obstacle, 15m, 100cm
The task
•Walk on a treadmill (self propelled)•Rear projected screen (77 cm, 85 degrees wide)•“infinite” shopping mall corridor
•Obstacle appeared at 5m or 15m for 1 second
•Square pillars with images of people (30cm or 70cm wide)
•Task: Would you have collided with the obstacle?•New path before each obstacle•Random angular offsets of paths
“Yes, collision” responses against closest distance to obstacle
How “big” do you feel? Distance with optimal decision (highest kappa)
How “good” a decision? Decision quality = maximum kappa (height)
Kappa coefficient of association
Collision envelope varied between subjects and with obstacle distance
Z19=3.44
p<0.001
No effect of obstacle size
22 subjects
Better decisions at smaller obstacle distance
Z19=4.07
p<0.0001
22 subjects
Some subjects had great difficulty at 15m
Do physical characteristics matter?
• Preferred walking speed, stride length
• Width at shoulder and of the arms
• Age
• Height, weight, body mass index (BMI)
Collision envelope was not predicted by physical characteristics
22 subjects
5m rs = 0.02, p=0.92
15m rs = 0.01, p=0.99
Collision envelope was (usually) larger than measured physical characteristics
22 subjects
Collision envelope equals body width
5m rs = -0.26, p=0.25
15m rs = +0.03, p=0.92
Further experiments
• Repeatability
• 15m, was task difficulty due to poor determination of heading?
• Does physical size not matter at all?
How repeatable were our results?
5m rs = 0.43, p=0.26
15m rs = 0.77, p=0.08
8 subjects
Compare distributionsNo significant differences (p>0.69)
15m obstacles: was task difficulty due to a problem determining heading?
15m obstacles: providing heading information improved task performance
z4 = 1.15, p = 0.25 z4 = 2.37, p = 0.025 subjects
0 20 40 60 80
first trial
with path
collision envelope (cm)
0.0 0.2 0.4 0.6 0.8 1.0
first trial
with path
kappa coefficient
Does physical size not matter at all?
Wings
0.0 0.2 0.4 0.6 0.8 1.0
first trial
wings
kappa coefficient0 20 40 60 80
first trial
wings
collision envelope (cm)
Does physical size matter?
z4 = 2.02, p = 0.04 z4 = 1.83, p = 0.07
Yes
5 subjects
Actual (half) width of the wings
Review of main results
• Effect of distance– collision envelope slightly larger; and – decision quality reduced at further distance
• Heading perception seems a limiting factor
• Physical characteristics not predictive, but
• Collision envelope can be manipulated
We evaluated …. • Collision detection• Subject’s perception of “size” (collision
envelope or safety margin)
While…. • Free viewing in “rich” virtual environment• Actually walking
But …• Stationary obstacles only• Single obstacles only
Thank you(for coming to the last presentation
at ARVO 2003)
Supported by NIH grant EY12890
The collision envelope
• We defined the collision envelope as the optimal decision point of the intra-class kappa coefficient
• This assumes that the cost of a false positive (avoidance when no risk) is the same as a false negative (collision)
The weighted kappa coefficient K0.1 places greater cost on false negative (collision)
K0.1 K0.5
5m 46cm 37cm
15m 65cm 46cm
On a treadmill
large obstacle, 5m, 25cm
large obstacle, 15m, -15cm