Demo Data from EDBT 2026 / reviewers in the wild / expert
Harvey S. Smallman
dblp:61/451
· DBLP profile ↗
4ranked-venue papers
0as first author
0since 2021 · last 2009
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 4Human-computer interaction and ubiquitous computing · 3
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
3 papers |
Virtual and augmented reality · 100% | |
| Human-computer interaction and pervasive computing
2 papers |
Usability and user experience research · 67% Immersive interaction · 33% |
Topics — the 8 heaviest of 9, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Virtual and augmented reality
depth perception |
0.2 | 3 | 2009 | Indoor vs. Outdoor Depth Perception for Mobile Augmented Reality · VR 2009 A Perceptual Matching Technique for Depth Judgments in Optical, See-Through Augmented Reality · VR 2006 Objective Measures for the Effectiveness of Augmented Reality · VR 2005 |
Immersive interaction
augmented reality |
0.1 | 1 | 2007 | Egocentric Depth Judgments in Optical, See-Through Augmented Reality · IEEE Trans. Vis. Comput. Graph. 2007 |
Virtual and augmented reality
augmented reality |
0.1 | 1 | 2006 | A Perceptual Matching Technique for Depth Judgments in Optical, See-Through Augmented Reality · VR 2006 |
Usability and user experience research › experimental design
human-subject experiments |
0.1 | 1 | 2006 | A Perceptual Matching Technique for Depth Judgments in Optical, See-Through Augmented Reality · VR 2006 |
Usability and user experience research
perceptual studies |
0.1 | 1 | 2006 | A Perceptual Matching Technique for Depth Judgments in Optical, See-Through Augmented Reality · VR 2006 |
Virtual and augmented reality › augmented reality
mobile augmented reality |
0.0 | 1 | 2009 | Indoor vs. Outdoor Depth Perception for Mobile Augmented Reality · VR 2009 |
Usability and user experience research › user study
user perception study |
0.0 | 1 | 2007 | Egocentric Depth Judgments in Optical, See-Through Augmented Reality · IEEE Trans. Vis. Comput. Graph. 2007 |
Virtual and augmented reality › augmented reality › augmented reality visualization
x-ray vision |
0.0 | 1 | 2006 | A Perceptual Matching Technique for Depth Judgments in Optical, See-Through Augmented Reality · VR 2006 |
Methods — techniques the papers use, named apart from their topics
user study · 0.1perceptual matching task · 0.1experimental design · 0.1verbal report · 0.1perceptual matching · 0.1blind walking · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2009 | Indoor vs. Outdoor Depth Perception for Mobile Augmented RealityabstractWe tested users' depth perception of virtual objects in our mobile augmented reality (AR) system in both indoor and outdoor environments using a depth matching task. The indoor environment is characterized by strong linear perspective cues; we attempted to re-create these cues in the outdoor environment. In the indoor environment, we found an overall pattern of underestimation of depth that is typical for virtual environments and AR systems. However, in the outdoor environment, we found that subjects overestimated depth. In addition, our synthetic linear perspective cues met with a measure of success, leading users to reduce their estimate of the depth of distant objects. We describe the experimental procedure, analyze the data, present the results of the study, and discuss the implications for mobile, outdoor AR systems. Mark A. Livingston, Zhuming Ai, J. Edward Swan II, Harvey S. Smallman |
VR | 4 |
| 2007 | Egocentric Depth Judgments in Optical, See-Through Augmented RealityabstractAbstract-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. Furthermore, 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 protocols for measuring egocentric depth judgments in both virtual and augmented environments, and discusses the well-known problem of depth underestimation in virtual environments. It then describes two experiments that measured egocentric depth judgments in AR. Experiment I used a perceptual matching protocol to measure AR depth judgments at medium and far-field distances of 5 to 45 meters. The experiment studied the effects of upper versus lower visual field location, the x-ray vision condition, and practice on the task. The experimental findings include evidence for a switch in bias, from underestimating to overestimating the distance of AR-presented graphics, at approximately 23 meters, as well as a quantification of how much more difficult the x-ray vision condition makes the task. Experiment II used blind walking and verbal report protocols to measure AR depth judgments at distances of 3 to 7 meters. The experiment examined real-world objects, real-world objects seen through the AR display, virtual objects, and combined real and virtual objects. The results give evidence that the egocentric depth of AR objects is underestimated at these distances, but to a lesser degree than has previously been found for most virtual reality environments. The results are consistent with previous studies that have implicated a restricted field-of-view, combined with an inability for observers to scan the ground plane in a near-to-far direction, as explanations for the observed depth underestimation. J. Edward Swan II, Eric Kolstad, Mark A. Livingston, Harvey S. Smallman |
IEEE Trans. Vis. Comput. Graph. | 5 |
| 2006 | A Perceptual Matching Technique for Depth Judgments in Optical, See-Through Augmented RealityabstractA 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. Furthermore, 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 environments. 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. J. Edward Swan II, Mark A. Livingston, Harvey S. Smallman, Dennis G. Brown, Yohan Baillot, Joseph L. Gabbard, Deborah Hix |
VR | 3 |
| 2005 | Objective Measures for the Effectiveness of Augmented RealityabstractAugmented reality (AR) systems present a mixture of virtual and real objects. The challenge for AR system evaluators is how to tell whether the virtual world is effective at conveying the sense of reality. It may never be possible or even necessary to determine whether the user is truly fooled in all situations or is merely suspending disbelief, but one can objectively measure the effectiveness of an AR environment with a task-based approach. We present the results of our first such experiment, involving low-level perceptual tasks of recognition and depth matching. Mark A. Livingston, Catherine A. Zanbaka, J. Edward Swan II, Harvey S. Smallman |
VR | 4 |