Distance Estimation in Real and Virtual Environments

2004 ◽  
Author(s):  
Jodie M. Plumert ◽  
Joseph K. Kearney ◽  
James F. Cremer
Keyword(s):  
Virtual Environments ◽  
Distance Estimation

How does presentation method and measurement protocol affect distance estimation in real and virtual environments?

2010 ◽  
Vol 7 (4) ◽  
pp. 1-18 ◽  
Author(s):  
Timofey Y. Grechkin ◽  
Tien Dat Nguyen ◽  
Jodie M. Plumert ◽  
James F. Cremer ◽  
Joseph K. Kearney
Keyword(s):  
Virtual Environments ◽  
Distance Estimation ◽  
Measurement Protocol ◽  
Presentation Method

Depth Perception Within Peripersonal Space Using Head-Mounted Display

2011 ◽  
Vol 20 (3) ◽  
pp. 254-272 ◽  
Author(s):  
Abdeldjallil Naceri ◽  
Ryad Chellali ◽  
Thierry Hoinville
Keyword(s):  
Individual Differences ◽  
Virtual Environments ◽  
Depth Perception ◽  
Distance Estimation ◽  
Peripersonal Space ◽  
Apparent Size ◽  
Open Loop ◽  
Head Mounted Display ◽  
The Rich

In this paper, we address depth perception in the peripersonal space within three virtual environments: poor environment (dark room), reduced cues environment (wireframe room), and rich cues environment (a lit textured room). Observers binocularly viewed virtual scenes through a head-mounted display and evaluated the egocentric distance to spheres using visually open-loop pointing tasks. We conducted two different experiments within all three virtual environments. The apparent size of the sphere was held constant in the first experiment and covaried with distance in the second one. The results of the first experiment revealed that observers more accurately estimated depth in the rich virtual environment compared to the visually poor and the wireframe environments. Specifically, observers' pointing errors were small in distances up to 55 cm, and increased with distance once the sphere was further than 55 cm. Individual differences were found in the second experiment. Our results suggest that the quality of virtual environments has an impact on distance estimation within reaching space. Also, manipulating the targets' size cue led to individual differences in depth judgments. Finally, our findings confirm the use of vergence as an absolute distance cue in virtual environments within the arm's reaching space.

scholarly journals Obstacles Affect Perceptions of Egocentric Distances in Virtual Environments

2021 ◽  
Vol 2 ◽  
Author(s):  
Daisuke Mine ◽  
Sakurako Kimoto ◽  
Kazuhiko Yokosawa
Keyword(s):  
Virtual Environments ◽  
Distance Perception ◽  
Distance Estimation ◽  
Egocentric Distance ◽  
Intermediate Space ◽  
Action Capability ◽  
Specific Effects ◽  
Transparent Barrier

Distance perception in humans can be affected by oculomotor and optical cues and a person’s action capability in a given environment, known as action-specific effects. For example, a previous study has demonstrated that egocentric distance estimation to a target is affected by the width of a transparent barrier placed in the intermediate space between a participant and a target. However, the characteristics of a barrier’s width that affect distance perception remain unknown. Therefore, we investigated whether visual and tactile inputs and actions related to a barrier affect distance estimation to a target behind the barrier. The results confirmed previous studies by demonstrating that visual and tactile presentations of the barrier’s width affected distance estimation to the target. However, this effect of the barrier’s width was not observed when the barrier was touchable but invisible nor when the barrier was visible but penetrable. These findings indicate the complexity of action-specific effects and the difficulty of identifying necessary information for inducing these effects.

Judging Perceived and Traversed Distance in Virtual Environments

1998 ◽  
Vol 7 (2) ◽  
pp. 144-167 ◽  
Author(s):  
Bob G. Witmer ◽  
Paul B. Kline
Keyword(s):  
Virtual Environments ◽  
Real World ◽  
Visual Cues ◽  
Large Scale ◽  
Distance Estimation ◽  
Movement Speed ◽  
The Real ◽  
Texture Density ◽  
Route Segment ◽  
Scale Spaces

The ability to accurately estimate distance is an essential component of navigating large-scale spaces. Although the factors that influence distance estimation have been a topic of research in real-world environments for decades and are well known, research on distance estimation in virtual environments (VEs) has only just begun. Initial investigations of distance estimation in VEs suggest that observers are less accurate in estimating distance in VEs than in the real world (Lampton et al., 1995). Factors influencing distance estimates may be divided into those affecting perceived distance (visual cues only) and those affecting traversed distance to include visual, cognitive, and proprioceptive cues. To assess the contribution of the various distance cues in VEs, two experiments were conducted. The first required a static observer to estimate the distance to a cylinder placed at various points along a 130-foot hallway. This experiment examined the effects of floor texture, floor pattern, and object size on distance estimates in a VE. The second experiment required a moving observer to estimate route segment distances and total route distances along four routes, each totaling 1210 feet. This experiment assessed the effects of movement method, movement speed, compensatory cues, and wall texture density. Results indicate that observers underestimate distances both in VEs and in the real world, but the underestimates are more extreme in VEs. Texture did not reliably affect the distance estimates, providing no compensation for the gross underestimates of distance in VE. Traversing a distance improves the ability to estimate that distance, but more natural means of moving via a treadmill do not necessarily improve distance estimates over traditional methods of moving in VE (e.g., using a joystick). The addition of compensatory cues (tone every 10 feet traversed on alternate route segments) improves VE distance estimation to almost perfect performance.

Landmark Direction and Distance Estimation in Large Scale Virtual Environments

1997 ◽  
Vol 41 (2) ◽  
pp. 1213-1217 ◽  
Author(s):  
Robert C. Allen ◽  
Daniel P. McDonald ◽  
Michael J. Singer
Keyword(s):  
Virtual Environments ◽  
Virtual Environment ◽  
Large Scale ◽  
Distance Estimation ◽  
Visual Display ◽  
Task Demands ◽  
Current Paper ◽  
Estimation Accuracy ◽  
Display Control

The current paper describes our classification of errors participants made when estimating direction and distances in a large scale (2000 m × 2000 m) Virtual Environment (VE). Two VE configuration groups (Low or High Interactivity) traversed a 400 m route through one of two Virtual Terrain's (Distinctive or Non-Distinctive or Terrain 1 and 2, respectively) in 100 m increments. The High VE group used a treadmill to move through the VE with head tracked visual displays; the Low VE group used a joystick for movement and visual display control. Results indicate that as experience within either terrain increased, participants demonstrated an improved ability to directionally locate landmarks. Experience in the environment did not affect distance estimation accuracy. Terrain 1 participants were more accurate in locating proximal, as opposed to distal, landmarks. They also overestimated distances to near landmarks and underestimated distances to far landmarks. In Terrain 2, the Low VE group gave more accurate distance estimations. We believe this result can be explained in terms of increased task demands placed on the High VE Group.

Correlations Between Physiological Response, Gait, Personality, and Presence in Immersive Virtual Environments

2012 ◽  
Vol 21 (2) ◽  
pp. 119-141 ◽  
Author(s):  
Lane Phillips ◽  
Victoria Interrante ◽  
Michael Kaeding ◽  
Brian Ries ◽  
Lee Anderson
Keyword(s):  
Stress Response ◽  
Virtual Environments ◽  
Virtual Environment ◽  
Distance Estimation ◽  
Estimation Accuracy ◽  
Personality Measures ◽  
Immersive Virtual Environments ◽  
Sense Of Presence ◽  
Significant Difference ◽  
Different Types

In previous work, we have found significant differences in the accuracy with which people make initial spatial judgments in different types of head-mounted, display-based immersive virtual environments (IVEs; Phillips, Interrante, Kaeding, Ries, & Anderson, 2010). In particular, we have found that people tend to less severely underestimate egocentric distances in a virtual environment that is a photorealistic replica of a real place that they have recently visited than when the virtual environment is either a photorealistic replica of an unfamiliar place, or a nonphotorealistically (NPR) portrayed version of a familiar space. We have also noted significant differences in the effect of environment type on distance perception accuracy between individual participants. In this paper, we report the results of two experiments that seek further insight into these phenomena, focusing on factors related to depth of presence in the virtual environment. In our reported first experiment, we immersed users (between-subjects) in one of the three different types of IVEs and asked them to perform a series of well-defined tasks along a delimited path, first in a control version of the environment, and then in a stressful variant in which the floor around the marked path was cut away to reveal a 20-ft drop. We assessed participants' sense of presence during each trial using a diverse set of measures, including: questionnaires, recordings of heart rate and galvanic skin response, and gait metrics derived from tracking data. We computed the differences in each of these measures between the stressful and nonstressful versions of each environment, and then compared the changes due to stress between the different virtual environment conditions. Pooling the data over all participants in each group, we found significant physiological indications of stress after the appearance of the pit in all three environments, but we did not find significant differences in the magnitude of the stress response between the different virtual environment locales. We also did not find any significant difference in the level of subjective presence reported in each environment. However, we did find significant differences in gait: participants in the photorealistic replica room showed a significantly greater reduction in stride speed and stride length between the control and pit version of the room than did participants in either the photorealistically rendered nonreplica environment or the NPR replica environment conditions. Our second experiment, conducted with a new set of participants, sought to more directly investigate potential correlations between distance estimation accuracy and personality, stress response, and reported sense of presence, comparatively across different immersive virtual environment conditions. We used pretest questionnaires to assess a variety of personality measures, and then randomly immersed participants (between-subjects) in either the photorealistic replica or photorealistic non-replica environment and assessed the accuracy of their egocentric distance judgments in that IVE, followed by control trials in a neutral, real-world location. We then had participants go through the same set of tasks as in our first experiment while we collected physiological measures of their stress level and tracked their gait, and we compared the changes in these measures between the neutral and pit-enhanced versions of the environment. Finally, we had people fill out a brief presence questionnaire.Analyzing all of these data, we found that participants made significantly greater distance estimation errors in the unfamiliar room environment than in the replica room environment, but no other differences between the two environments were significant. We found significant positive correlation between several of the personality measures, but we did not find any notable significant correlations between personality and presence, or between either personality or presence and gait changes or distance estimation accuracy. These results suggest to us that the relationship between personality, presence, and performance in IVEs is complicated and not easily captured by existing measures.

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