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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.

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Presentation on theme: "Perceived collision with an obstacle in a virtual environment Russell L Woods, Jennifer C Shieh Laurel Bobrow, Avni Vora, James Barabas, Robert B Goldstein."— Presentation transcript:

1 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

2 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

3 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)

4 Are potential-collision decisions based on physical size? (i.e. how big you are)

5 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

6 Closest distance to obstacle

7 Some obstacles crossed the path

8 Obstacle appearance distance

9 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

10 small obstacle, 5m, 55cm

11 large obstacle, 15m, 100cm

12 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

13 “Yes, collision” responses against closest distance to obstacle

14 How “big” do you feel? Distance with optimal decision (highest kappa) How “good” a decision? Decision quality = maximum kappa (height) Kappa coefficient of association

15 Collision envelope varied between subjects and with obstacle distance Z 19 =3.44 p<0.001 No effect of obstacle size 22 subjects

16 Better decisions at smaller obstacle distance Z 19 =4.07 p< subjects

17 Some subjects had great difficulty at 15m

18 Do physical characteristics matter? Preferred walking speed, stride length Width at shoulder and of the arms Age Height, weight, body mass index (BMI)

19 Collision envelope was not predicted by physical characteristics 22 subjects 5m r s = 0.02, p= m r s = 0.01, p=0.99

20 Collision envelope was (usually) larger than measured physical characteristics 22 subjects Collision envelope equals body width 5m r s = -0.26, p= m r s = +0.03, p=0.92

21 Further experiments Repeatability 15m, was task difficulty due to poor determination of heading? Does physical size not matter at all?

22 How repeatable were our results? 5m r s = 0.43, p= m r s = 0.77, p= subjects Compare distributions No significant differences (p>0.69)

23 15m obstacles: was task difficulty due to a problem determining heading?

24 15m obstacles: providing heading information improved task performance z 4 = 1.15, p = 0.25z 4 = 2.37, p = subjects

25 Does physical size not matter at all? Wings

26 Does physical size matter? z 4 = 2.02, p = 0.04z 4 = 1.83, p = 0.07 Yes 5 subjects Actual (half) width of the wings

27 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

28 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

29 Thank you (for coming to the last presentation at ARVO 2003) Supported by NIH grant EY12890

30

31 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)

32 The weighted kappa coefficient K 0.1 places greater cost on false negative (collision) K 0.1 K 0.5 5m46cm37cm 15m65cm46cm

33 On a treadmill

34 large obstacle, 5m, 25cm

35 large obstacle, 15m, -15cm


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