A Perceptual Matching Technique for Depth Judgments in Optical, See-Through Augmented Reality
J. Edward Swan II, Mark A. Livingston, Harvey S. Smallman, Dennis Brown, Yohan Baillot, Joseph L. Gabbard, and Deborah Hix. A Perceptual Matching Technique for Depth Judgments in Optical, See-Through Augmented Reality. In Technical Papers, Proceedings of IEEE Virtual Reality 2006, pp. 19–26, IEEE Computer Society, March 2006.
Winner of an Honorable Mention award at IEEE Virtual Reality 2006.
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Abstract
A fundamental problem in optical, see-through augmented reality (AR) is characterizing how it affects the perception of spatial layout and depth. This problem is important because AR system developers need to both place graphics in arbitrary spatial relationships with real-world objects, and to know that users will perceive them in the same relationships. Fur-thermore, AR makes possible enhanced perceptual techniques that have no real-world equivalent, such as x-ray vision, where AR users are supposed to perceive graphics as being located behind opaque surfaces. This paper reviews and discusses techniques for measuring egocentric depth judgments in both virtual and augmented envi-ronments. It then describes a perceptual matching task and experimental design for measuring egocentric AR depth judgments at medium- and far-field distances of 5 to 45 meters. The experiment studied the effect of field of view, the x-ray vision condition, multiple distances, and practice on the task. The paper relates some of the findings to the well-known problem of depth underestimation in virtual environments, and further reports evidence for a switch in bias, from underestimating to overestimating the distance of AR-presented graphics, at 23 meters. It also gives a quantification of how much more difficult the x-ray vision condition makes the task, and then concludes with ideas for improving the experimental methodology.
Additional Information
Acceptance rate: 28% (27 out of 95), Award rate: 11% (3 out of 27)
BibTeX
@InProceedings{IEEEVR06-pmt,
author = {J. Edward {Swan~II} and Mark A. Livingston and Harvey S. Smallman and
Dennis Brown and Yohan Baillot and Joseph L. Gabbard and Deborah Hix},
title = {A Perceptual Matching Technique for Depth Judgments in Optical,
See-Through Augmented Reality},
booktitle = {Technical Papers, Proceedings of IEEE Virtual Reality 2006},
year = 2006,
location = {Alexandria, Virginia, USA},
date = {March 25--29},
month = {March},
publisher = {IEEE Computer Society},
pages = {19--26},
wwwnote = {<b>Winner of an Honorable Mention award at IEEE Virtual Reality 2006</b>.},
abstract = {
A fundamental problem in optical, see-through augmented reality (AR)
is characterizing how it affects the perception of spatial layout and
depth. This problem is important because AR system developers need to
both place graphics in arbitrary spatial relationships with real-world
objects, and to know that users will perceive them in the same
relationships. Fur-thermore, AR makes possible enhanced perceptual
techniques that have no real-world equivalent, such as x-ray vision,
where AR users are supposed to perceive graphics as being located
behind opaque surfaces.
This paper reviews and discusses techniques for measuring egocentric
depth judgments in both virtual and augmented envi-ronments. It then
describes a perceptual matching task and experimental design for
measuring egocentric AR depth judgments at medium- and far-field
distances of 5 to 45 meters. The experiment studied the effect of
field of view, the x-ray vision condition, multiple distances, and
practice on the task. The paper relates some of the findings to the
well-known problem of depth underestimation in virtual environments,
and further reports evidence for a switch in bias, from
underestimating to overestimating the distance of AR-presented
graphics, at ~23 meters. It also gives a quantification of how much
more difficult the x-ray vision condition makes the task, and then
concludes with ideas for improving the experimental methodology.
},
}