fish tank vr

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Published on November 12, 2007

Author: Haralda

Source: authorstream.com

Slide1:  Fish Tank Virtual Reality Colin Ware and Kevin Arthur Faculty of Computer Science University of New Brunswice 가상 현실 입문 Contents:  Contents What is “Fish Tank VR” ? Advantages over immersion VR. Design properties of Fish Tank VR. Experiment 1 : Subjective Impressions of 3D. Experiment 2 : Tracing Tree Paths. Conclusion. What is “Fish Tank VR” ?:  What is “Fish Tank VR” ? The head coupled system including a monitor, a device for measuring head position, and stereo goggles [Fig 1.] Variables that experiments investigate whether or not the perspective view is coupled to the actual viewpoint of the observer. whether stereopsis is employed. Advantages over immersion VR(1):  Advantages over immersion VR(1) Resolution In immersion VR, given the typical resolution of current displays each pixel will subtend 12 minutes of arc. Depth-of-Field Without directly measuring the focal length of the observer’s lens, cannot take the depth-of-field directly into accounting in creating images for VR. Advantages over immersion VR(2):  Advantages over immersion VR(2) Stability in the Presence of Eye Movements A 40 deg eye movement result in a 3.8 mm translation of the center of the lens. Integration of the VR Workspace with the Everyday Workspace Design properties of Fish Tank VR(1):  Design properties of Fish Tank VR(1) Factors leading to the subjective impression of 3D space Objects Fig 2. and Fig 3. Depth-of-Field made the background out of fuzzy discs, to give the illusion of depth-of-field Shading Design properties of Fish Tank VR(2):  Design properties of Fish Tank VR(2) Spatio-Temporal Accuracy in Head Tracking 3Space Isotrak which may be as much as 80 msec behind the current position ADL-1 which is 2 ms behind the current position Stereo Display StereoGraphics CristalEyes stereo system : ability to display 120 frames/sccone High Frame Rate maximum of 60HZ Experiment 1 :  Experiment 1 Subjective Impressions of 3D Experimental Conditions 1. Picture 2. Stereo only 3. Head Coupled Monocular 4. Head Coupled Binocular 5. Head Coupled + Stereo Results From Experiment 1:  Results From Experiment 1 All Subjects 1 2 3 4 5 All 1 Picture 43% 1% 0% 7% 12% 2 Stereo only 57% 7% 11% 0% 19% 3 HC monocular 96% 93% 29% 61% 70% 4 HC binocular 100% 89% 71% 68% 82% 5 HC + stereo 93% 100% 39% 32% 66% Experiment 2:  Experiment 2 Tracing Tree Paths Recurrence relation for Tree consturction HorizontalSpacing(root) = 8.0cm VerticalSpacing(root) = 8.0cm HorizontalSpacing(child) = 0.7*HorizontalSpacing(root) VerticalSpacing(child) = 0.7*VerticalSpacing(root) Y(child) = Y(parent) + VerticalSpacing(1.0+Rand(0*0.25) X(child) = X(parent) + HorizontalSpacing*Rand() Z(child) = Z(parent) + HorizontalSpacing*Rand() Task domain of Experiment 2:  Task domain of Experiment 2 Medical imaging where doctors may wish to trace blood vessels in brain scan data 3D software visualization where software engineers may wish to trace object dependencies between software modules represented as networks in 3D space. Result From Experiment 2:  Result From Experiment 2 Timing data times(sec) 1. Picture 7.50 2. Stereo only 8.09 3. HC monocular 8.66 4. HC binocular 9.12 5. HC + stereo 6.83 Error data % (errors) 1. Picture 21.8 2. Stereo only 14.7 3. HC monocular 3.7 4. HC binocular 2.7 5. HC + stereo 1.3

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