the effect of feedback training on distance estimation in virtual environments

APPLIED COGNITIVE PSYCHOLOGYAppl. Cognit. Psychol. 19: 1089–1108 (2005)

Published online 16 June 2005 in Wiley InterScience(www.interscience.wiley.com) DOI: 10.1002/acp.1140

The Effect of Feedback Training on DistanceEstimation in Virtual Environments

ADAM R. RICHARDSON* and DAVID WALLER

Miami University, USA

SUMMARY

It is often noted that distances are significantly underestimated in computer-simulated (virtual)environments. Two experiments examine observers’ ability to use error corrective feedback toimprove the accuracy of judgments of egocentric and exocentric distances. In Experiment 1,observers viewed objects in an immersive virtual environment and estimated their distance through ablindfolded walking task. Different groups received feedback on either egocentric, exocentric ornone of these judgments. Receiving feedback improved observers’ ability to estimate only thosedistances for which feedback was provided. These effects persisted for at least 1 week. InExperiment 2, observers estimated egocentric distance by means of both a direct and indirectwalking task. Receiving feedback on the direct walking task predominantly improved directestimates and not indirect estimates. These findings suggest that although feedback training offersa relatively straightforward and immediate way of overcoming problems of distance estimation, itseffects are specific to both the type of judgment and the type of response. Copyright # 2005 JohnWiley & Sons, Ltd.

Computer-simulated ‘virtual’ environments (VEs) hold potential for training people on

tasks in environments and situations that are rare, remote, costly or dangerous (Bliss,

Tidwell, & Guest, 1997; Darby, 2000; Seidel & Chatelier, 1997). However, much of the

promise of this technology has been tempered by the fact that users of such systems often

cannot accurately estimate modelled distances. Estimates of absolute egocentric distances

(those from an observer to an external object) are commonly underestimated by as much

as 50% (J. M. Knapp, unpublished PhD dissertation, 1999; Loomis & Knapp, 2003;

Thompson et al., 2004; Witmer & Kline, 1998; Witmer & Sadowski, 1998), an effect that

makes it difficult for developers to depict large-scale spaces realistically (Loomis &

Knapp, 2003). Perhaps surprisingly, judgments of exocentric distances (those between two

objects) in VEs, although less studied, appear to be much more accurate—generally

within 90% of the modelled distance—than those of egocentric distances (Waller, 1999).

The causes of the underestimation of egocentric distances in VEs are not yet fully

understood. Most investigators have suggested technological factors associated with VEs

such as the limited field of view available in head mounted displays (HMDs) (Loomis &

Knapp, 2003; Plumert, Kearney, & Cremer, 2004; see also Wu, Ooi, & He, 2004), errors in

Copyright # 2005 John Wiley & Sons, Ltd.

*Correspondence to: Adam R. Richardson, 236 B Benton Hall, Department of Psychology, Miami University,Oxford, OH 45056, USA. E-mail: [email protected]

accommodation (Witmer & Sadowski, 1998), the lack of accurate binocular stereo images

in HMDs (Witmer & Sadowski, 1998), and limits on the resolution and quality of images

displayed in HMDs (Thompson et al., 2004). However, the findings from these studies

have not been conclusive. For example, in one recent study, Thompson et al. (2004) varied

the visual fidelity of a VE, ranging from wire-frame representations to photorealistic

environments. Despite the differences in realism and technological sophistication,

participants’ distance estimates revealed compression (approximately 50% of the actual

distance) in each of the three VEs included in this study, but no compression of distance

estimates made in the actual environment.

In the present article, we adopt a different, perhaps more immediately pragmatic

approach to the problem of underestimated distances in VEs. Rather than focusing on the

technological aspects of VE systems and attempting to create a higher-fidelity stimulus

environment, we examine how information about distance can be conveyed to the user

after (or as) information about the environment is mentally encoded. This examination can

be understood in the context of theoretical approaches to distance perception that posit the

existence of several psychological processes that intervene between the perception of an

object and the estimation of a distance to it (Neisser, 1967; Philbeck & Loomis, 1997; but

see Gibson, 1979). According to this approach, sensory (primarily visual) information that

is available from the environment or is available from an observer’s interaction with the

environment (see Cutting & Vishton, 1995, for a review of environmental cues to distance)

is encoded, resulting in a percept of the location of a target object (Loomis, Da Silva,

Philbeck, & Fukusima, 1996). This percept may be subsequently transferred to memory

when sensory information is no longer available. When a task requires the estimation of a

distance to the target location, a response is selected. This process of response selection

and execution may be influenced by response calibration mechanisms, high-level

strategies or other conceptual factors. Because, by this account, several psychological

processes intercede between the perception and the estimation of a distance, it is clear that

a distance estimate by itself is not a pure measure of perceived distance. By the same

token, manipulations that enhance distance estimation skill may work because they exert

their effort on one (or more) of several mental processes. For example, observers may

improve their ability to estimate a distance because they acquire high-level cognitive

strategies to make such an estimate—not because they perceive the distance differently.

For many VE applications, training systems that result in enhanced accuracy of distance

estimates can still be useful, even if the underlying perceptions of distance are not altered

by training.

One straightforward means of affecting estimates of distance is to train people by means

of error-corrective feedback. Although feedback training is effective in real-world

environments (G. L. Allen & M. A. Rashotte, submitted; Training metric accuracy in

distance estimation skill; Pichves vs. Words; Gibson & Bergman, 1954; Gibson, Bergman,

& Purdy, 1955), its utility in VEs has not been adequately investigated. Past research in

real-world situations investigating egocentric distance estimation has shown that indivi-

duals’ verbal estimates of distance are typically underestimated by approximately 90% of

the true distance (Foley, Ribeiro-Filho, & Da Silva, 2004; Gibson & Bergman, 1954).

However, when people are provided feedback about their errors, accuracy is improved,

and the variance of their estimations is reduced (Gibson, 1953; Gibson et al., 1955; Gibson

& Bergman, 1954). For example, Gibson and Bergman (1954) asked participants to make

judgments of absolute egocentric distance to targets and provided them with feedback

after each judgment. Feedback training enabled their participants’ distance estimates to

1090 A. R. Richardson and D. Waller

Copyright # 2005 John Wiley & Sons, Ltd. Appl. Cognit. Psychol. 19: 1089–1108 (2005)

improve immediately, from 93% of the actual distance before training to approximately

102% after training.

Although Gibson and her colleagues showed the effects of feedback training to be

immediate, at least one other study has shown them to be transient. Horowitz and Kappauf

(1945), examined the retention of feedback training on distance estimation, and found that

60 days after successful feedback training, much of the initial effect of feedback training

had been lost, with observers again showing underestimation and increased error in their

distance estimates. To our knowledge, no other studies have investigated the longevity of

feedback training’s effect on distance estimates in either natural or computer-generated

environments. As a result, it is possible that the effect of feedback training is short-lived,

and perhaps does not extend very far beyond the training situation. To examine this

possibility, we assessed the effects of feedback 1 week after training.

In addition to determining the value of feedback training in enhancing the accuracy of

users’ estimates of distance in VEs, it is also important to investigate its possible

limitations. Such potential limitations include the possibility that the effects of training

are specific to the type of trained stimuli, and the possibility that training will not transfer

well to novel situations or novel tasks. In Experiment 1, we examine the possible

specificity of feedback training by investigating whether feedback about one type of

distance (e.g. egocentric) generalizes to judgments of another type (e.g. exocentric). In

Experiment 2, we further examine whether feedback provided as a result of a particular

type of response (direct blindfolded walking) generalizes to responses of another type

(indirect blindfolded walking).

EXPERIMENT 1

Experiment 1 was designed to address three questions. First, we were interested in whether

the accuracy of distance estimates in VEs improves when users are provided error-

corrective feedback. This question was addressed separately for egocentric and exocentric

distance estimates (which all participants made) by comparing performance between

groups that received feedback training and a control group that did not. Based on Gibson

and her colleagues’ findings on the effect of feedback in natural environments (Gibson,

1953; Gibson & Bergman, 1954), we anticipated that feedback would be similarly

effective in VEs.

Second, Experiment 1 was designed to assess whether the effects of feedback training

persist beyond the immediate training situation. All participants returned 1 week after the

initial training session and again estimated distances in the VE. We assessed the duration

of the effect of feedback training by comparing pre-training performance, to performance

1 week after training.

Finally, Experiment 1 was designed to investigate one way in which the effect of

feedback training may be specific. We were interested in whether feedback about one type

of distance judgment (egocentric or exocentric) influences accuracy of judgments of

another type. In addition to shedding light on a possible limitation of feedback training in

applications that use VE technology, investigating this issue can advance our under-

standing of how egocentric and exocentric distance estimates are mentally processed.

More specifically, several prior findings have suggested that the psychological processes

that underlie egocentric distance estimation may be separable from those that underlie

exocentric distance estimates. For example, as noted previously, although egocentric

Distance estimation in VEs 1091


distances are routinely underestimated in VEs, estimates of exocentric distances have been

shown to be relatively accurate—on average within 90% (Waller, 1999). Likewise,

experiments in real-world environments have shown that exocentric distances can be

underestimated even when the estimates of egocentric distance to the endpoints of the

exocentric interval are veridical (Loomis et al., 1996; Loomis, Da Silva, Fujita, &

Fukusima, 1992). Thus, it is an open question whether manipulations that affect estimates

of egocentric (or exocentric) distances will show comparable effects on estimates of

exocentric (or egocentric) distances.

We measured participants’ distance estimates by means of an open-loop walking

paradigm in which an observer, after initially seeing a target, walks the distance to the

target location while blindfolded. We preferred this type of measurement over verbal

reports of distances because verbal estimates are clearly influenced by the observer’s

understanding of measurement units, and are likely subject to higher-level cognitive

strategies and biases (Gilinski, 1951; Harway, 1963). Although motoric responses, such as

blindfolded walking, require and are influenced by response calibration processes, these

processes are generally well-practised, precise, and accurate (Loomis et al., 1992).

Motoric responses are thus commonly used to measure distance estimates because they

provide a more precise, less biased measure of perceived distance than verbal estimates

(Ellard & Shaughnessy, 2003; Elliot, 1987; J. M. Knapp, unpublished PhD dissertation,

1999; Loomis et al., 1993, 1996; Loomis & Knapp, 2003; Ooi, Wu, & He, 2001; Philbeck,

Loomis, & Beall, 1997; Rieser, Ashmead, Talor, & Younquist, 1990; Sinai, Ooi, & He,

1998; Thompson et al., 2004; Thomson, 1983; Witmer & Sadowski, 1998).

Method

Observers

Twenty-four (12 male, 12 female) individuals participated in the study. Their average age

was 21.67 years (SD¼ 3.05). Three gender-balanced groups, each with eight participants,

composed the three main conditions of the experiment. All participants had normal or

corrected to normal vision. Individuals participated in the experiment in return for either

$15 or for credit towards a requirement in their introductory psychology course.

Stimuli and apparatus

The VE consisted of a textured ground plane upon which, at the beginning of every trial, a

set of three target posts, each modelled to be 100 cm tall and of differing colour (red,

green, blue), was randomly placed. All judged distances were either 75 cm, 125 cm,

225 cm, 350 cm, or 425 cm. The targets were placed in the environment so that each

judged egocentric or exocentric distance had an equivalent exocentric or egocentric

distance (see Figure 1).

The environment was presented using a Virtual Research V8 HMD with interlaced

640� 480 resolution and 50� horizontal field of view. The display allowed for a binocular

stereo image of the scene to be displayed (i.e. separate images were projected to each eye,

accounting for the participant’s inter-pupillary distance). Height above the simulated

ground plane was set to the participant’s standing eye-height. Mounted on the HMD was

an Intersense InertiaCube2 tracker. This tracker was used to update the orientation of the

visual image as the participant moved his or her head with an accuracy of 1�.The VE was rendered using an Intel Pentium 4 chipset and an Nvidia Gforce2 MX

graphics card, allowing for updating of the graphics, display and sensor data at 72 Hz.



Assignment to each condition, randomization and presentation of the stimuli as well as

collection of distance estimates and delivery of proper feedback when necessary were was

controlled through a scripting facility in the Python programming language, supplemented

with a utility module designed specifically for VE applications. Participants’ locations

(and hence their distance estimates) were determined by means of a WorldViz PPT 1.0

passive video tracking system that triangulated the position (within 1 mm) of an LED

worn on the observer’s head. The information from the position tracker was then

incorporated into the Python routine, and estimates of distance were recorded to an

external file.

Participants gave their distance estimates by walking blindfolded along a narrow (1 cm

thick, 61 cm wide) foam pathway on the lab floor. Participants’ vision was occluded (i.e. a

dark screen was displayed in the HMD) while they provided their responses. Because

blindfolded observers could easily determine whether or not they stood on the foam, the

pathway effectively kept participants walking in one direction without veering.

Procedure

Instruction and training phase. Each participant was met outside of the laboratory where

he or she consented to participate in the experiment. Standing eye-height and inter-

pupillary distance of each observer was obtained in the lab prior to the delivery of task

instructions.

After being introduced to the experiment, each participant was shown a full-scale model

of one of the target posts to allow them to familiarize themselves with its modelled size.

The participant was then trained in how to walk along the pathway and return to the origin

Figure 1. Stimulus configurations in Experiment 1. For egocentric trials observers judged one of fivedistances separating themselves from the target post. For exocentric trials the midpoint of theinterval between the two target posts was placed at one of the five judged egocentric distances, and

this interval was orthogonal to the line of sight to the midpoint



without vision. This training consisted of escorting the blindfolded participant forward

along the path, then stopping and walking backwards slowly to the start of the pathway

several times. This was done to reduce variance in walking estimates that might be

associated with unfamiliarity with the task, as well as to develop a level of trust between

the experimenter and the participant during the blindfolded portions of the trials. Once this

pre-training was completed, the participant performed four practice trials for each type of

distance estimate in order to become familiar with the experimental procedures. No

feedback about errors in the participant’s distance estimates was provided at this point.

On each trial, participants viewed the environment while standing with their feet against

the edge of the foam pathway. While observing the stimulus, participants were instructed

not to move their feet from this position, though no other restrictions were placed on their

movement. Instructions for the blindfolded walking responses of egocentric distance

directed the participant to walk confidently and without hesitation straight ahead from

their point of observation along the pathway for the distance that they had observed,

imagining that the post’s location was directly in front of them and to stop when they

thought they were standing on the target’s location. Instructions for the blindfolded walking

responses of exocentric distance directed the participant to imagine being at one of the

target locations rather than their point of observation, to walk confidently and without

hesitation from that location the distance to another target location, and to stop when they

thought they were standing on the target’s location (e.g. standing at the green post walk the

distance to the blue post, see Figure 2). Observers were not given a specific time limit in

Figure 2. Stimulus configuration in Experiment 1. A view of the environment from the participant’sviewpoint, noting the posts of interest for an exocentric trial. (Unlike this reproduction, the

environment was presented in colour)



which to give their response, but they were instructed that the experimenter was interested

in their initial reactions and not to take too much time with any one estimate.

Pre-test. A pre-test then assessed the accuracy of the observers’ distance estimates in the

absence of formal training. The data collected from this portion of the experiment served

as a baseline for assessing the impact of the feedback training. The pre-test consisted of 15

(three replications of each of the five distances) estimates of egocentric distance and 15

estimates of exocentric intervals for each participant. These trials were blocked by

judgment type (egocentric/exocentric) and the order of blocks was counterbalanced across

participants. Within a block, to-be-estimated distances were randomized separately for

each subject.

Feedback training. After the pre-test, observers were given training based on their

experimental condition. Observers judged another set of 15 trials, each with novel

arrangements of the target locations. One third of the observers judged only 15 egocentric

distances and were given feedback after each estimate, one third judged only 15 exocentric

distances and were given feedback after each estimate, and one third judged 15 distances

composed of both egocentric and exocentric distances, and were given no feedback. All

feedback was given in the form of a schematic depiction of the scene in the headset that

showed the participant’s starting location and target location marked accordingly (see

Figure 3). A bar extended from the depicted starting location towards the target location,

representing the observer’s estimated distance to the target location (i.e. the distance they

had walked). In addition, numerical values of the actual and estimated distances were

provided in text on the display (e.g. ‘estimated distance¼ 3.65 m; actual dis-

tance¼ 4.25 m’).

Figure 3. Information provided to observers during feedback training. Egocentric feedback fromExperiments 1 and 2 is pictured on the left and exocentric feedback from Experiment 1 is picturedon the right. Feedback took the form of a schematic depiction of the scene in the headset showingthe participant’s starting location and target location marked accordingly. A bar extended from thestarting location toward the target location representing the observer’s estimated distance to the targetlocation (i.e. the distance they had walked). In addition, a numerical value of the difference indistance was provided in text on the display (e.g. estimated distance¼ 0.93 m, actual dis-

tance¼ 1.25 m)



Immediate post-test and retention post-test. After the feedback training, an immediate

post-test was administered to assess the effect of training. A new set of 30 trials (15

egocentric and 15 exocentric) with novel target locations was presented to the observers.

Finally, the observers returned after 1 week and provided another set of 30 distances

estimates. We call this set of trials the retention post-test, and it served to determine if the

effect of training persisted for at least 1 week. The procedures for the immediate post-test

and retention post-test phases of the experiment were identical to those used for the pre-

test. Participants were offered practice trials when they returned after the 1-week

intersession interval but none accepted, as they all reported fully remembering the

procedures.

Design

The experiment represents a 3 (phase: pre-test vs. immediate post-test vs. retention post-

test)� 3 (feedback type: egocentric vs. exocentric vs. none)� 2 (judgment type: ego-

centric vs. exocentric) mixed design. All factors except feedback type were manipulated

within subjects. The main dependent variable used in the analyses was observers’ mean

proportional error in judgment, defined as the judged distance divided by the actual

distance (e.g. a result of 0.5 indicates that the estimated distance was half of the modelled

distance, and a result of 1 represents no error in judgment). For all of the following

analyses, a mean proportional error in judgment score was determined for each participant,

based on three replications of each of the five-judged distances. Other measures such as the

slope and r2 derived from individually regressing each participant’s estimates on the actual

distances led to identical conclusions as those reported here.

Results

Five observations from four individuals (0.2% of the total number of trials) indicated

distance estimates that were beyond the boundaries of the lab and were likely a result of

computer error. These trials were removed from all analyses. Parameter estimates are

reported along with the width of their associated 95% confidence intervals. The

magnitudes of effects are described with the labels suggested by Cohen (1988).

The effect of feedback on the accuracy of distance judgments

Feedback training improved the accuracy of both absolute egocentric and exocentric

distance judgments in VEs. We discuss each type of judgment in turn.

Judgments of egocentric distances. As the black and white bars in Figure 4 depict,

participants who received egocentric feedback altered their estimates of egocentric

distances from 0.58 (� 0.14 for a 95% confidence interval) in the pre-test to 1.02

(� 0.19) in the immediate post-test, which represents a large (d¼ 2.80) change of 44%

(� 0.14), nearly all of this change represents improvement. These results contrasted with

the no feedback group, for whom accuracy improved only 4% (� 0.16) from 0.76

(� 0.23) to 0.80 (� 0.26). This was a small effect (d¼ 0.11). These observations were

confirmed in a 2� 2 mixed effects analysis of variance (ANOVA) on the factors of phase

(pre-test, immediate post-test) and feedback type (egocentric, none). The critical result

from this analysis was a significant interaction between phase and feedback

(F(1, 14)¼ 8.64, MSE¼ 0.034, p¼ 0.01, f¼ 1.60).



Judgments of exocentric distances. As the grey and white bars in Figure 5 show,

participants who received exocentric feedback improved their estimates 8% (� 0.10)

from 0.90 (� 0.15) in the pre-test to 0.98 (� 0.08) after training. Somewhat surprisingly,

estimates from participants in the no feedback group rose 19% (� 0.15) from 0.96

(� 0.21) to 1.15 (� 0.33), representing a tendency for these participants to overestimate

exocentric distances after training. These results were confirmed in a 2� 2 mixed effects

ANOVA on the factors of phase (pre-test, immediate post-test) and feedback type

(exocentric, none). The only significant effect was that of phase, indicating that on

average, between the pre-test and immediate post-test the accuracy of exocentric distance

judgments increased (F(1, 14)¼ 8.13, MSE¼ 0.017, p< 0.05, f¼ 1.61).

The persistence of improved distance estimation

The results of these analyses were clear: Improved accuracy of absolute distance

judgments in VEs after feedback training persisted for at least 1 week. As with the

previous analyses, we discuss judgments of egocentric and exocentric distances in turn.

Judgments of egocentric distances. As Figure 4 depicts, estimates from the participants

who received egocentric feedback showed a showed a large (d¼ 2.64) increase of 39%

Egocentric Judgments

Phase

Pre-Test Post-Test Retention Post-Test

Mea

nP

ropo

rtio

nalE

rror

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

Veridical

EgocentricExocentricNone

Feedback Group

Figure 4. Mean proportional error (error bars represent one standard error) in egocentric distanceestimates from Experiment 1, defined as (estimated distance/actual distance) a function of phase andfeedback group. Values lower than 1 are indicative of underestimation and values above 1 indicate

overestimations



(� 0.17) from 0.58 (� 0.14) in the pre-test to 0.97 (� 0.16) in the retention post-test. In

general, the no feedback group’s estimates remained relatively steady, showing a small

(d¼ 0.25) improvement of 4% (� 0.10) from 0.76 (� 0.23) in the pre-test to 0.80

(� 0.19) in the retention post-test. To confirm these results, a 2� 2 mixed effects ANOVA

was conducted on the factors of phase (pre-test, retention post-test) and feedback type

(egocentric, none). Of primary interest was a significant interaction between phase and

feedback type, indicating that the level of improvement in the accuracy of egocentric

distance judgments was significantly larger for the egocentric feedback group than for the

no feedback group (F(1, 14)¼ 5.90, MSE¼ 0.037, p< 0.05, f¼ 1.55).

Judgments of exocentric distances. Estimates from the exocentric feedback group

increased 15% (� 0.16), from 0.90 (� 0.14) in the pre-test to 1.05 (� 0.13) in the

retention post-test (see Figure 5). This was a large effect (d¼ 1.15). Surprisingly, the no

feedback group showed a 26% (� 0.14) change in their level of performance, from a pre-

test level of 0.96 (� 0.20) to 1.22 (� 0.20) in the retention post-test. This was also a large

effect (d¼ 1.34).

Exocentric Judgments

Phase

Pre-Test Post-Test Retention Post-Test

Mea

nP

ropo

rtio

nalE

rror

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

Veridical

EgocentricExocentricNone

Feedback Group

Figure 5. Mean proportional error (error bars represent one standard error) in exocentric distanceestimates from Experiment 1, defined as (estimated distance/actual distance) a function of phase andfeedback group. Values lower than 1 are indicative of underestimation and values above 1 indicate

overestimations



The specificity of feedback’s effects

In order to determine the degree to which egocentric feedback improved exocentric

estimates (and vice versa) we defined a new dependent variable that allowed direct

comparison of egocentric and exocentric distance errors. This new dependent variable

represented the amount of improvement provided by feedback training. We used a

measure of relative improvement that indicates how much one approaches veridical

judgments relative to one’s baseline performance. In addition, we examined an absolute

measure of improvement, defined as the absolute value of 1-immediate post-test error.

These analyses produced identical conclusions to those reported here. Our measure of

relative improvement was defined as:

loge

j1-pre-test errorjj1-immediate post-test errorj

� �

For this measure, a positive score represents improvement, while a score of 0 indicates no

improvement and negative scores indicate performance decrements. To further explain this

measure, consider the case of an observer who improves his estimates from 50% to 75% of

the actual distance after feedback training, while another improves her estimates from 90%

to 95% of the actual distance. The first observer has made an improvement of 25% while the

other only improved by 5%, however our measure of relative improvement would indicate

equivalent improvement, because each observer improved his or her estimates by 50% of

the interval that was left for improvement based on their original estimates.

As the first four bars of Figure 6 illustrate, egocentric feedback improved primarily

judgments of egocentric distances and exocentric feedback improved primarily judgments

of exocentric distances. Egocentric feedback resulted in a relative improvement of 0.90

(� 0.63) for judgments of egocentric distances, and only �0.48 (� 0.65) for judgments of

exocentric distances. Similarly, exocentric feedback resulted in a relative improvement of

0.86 (� 0.88) for judgments of exocentric distances, and only 0.34 (� 0.36) for judgments

of egocentric distances. This relationship was verified by a significant crossover interac-

tion between the factors of judgment type and feedback type (F(1, 14)¼ 16.39,

MSE¼ 0.44, p< 0.01, f¼ 0.69).

Discussion

We investigated three questions with Experiment 1. First we were interested in the ability

of feedback training to improve observers’ ability to estimate distances in a VE accurately.

Our results replicated previous findings that prior to training, absolute egocentric distance

estimates in VEs are significantly compressed. In this case, estimates generally repre-

sented only 58% of the actual distances. However, unlike previous studies, we were able to

correct these estimates to nearly veridical judgments with only a brief period of feedback

training. This experiment also replicated previous findings that show exocentric distance

estimates in VEs are fairly accurate and generally judged, even without training, to be

approximately 90% of the actual distance (Waller, 1999). Our findings—especially for

egocentric estimates—have direct implications for the use of VEs for simulation, training,

production, tele-operation and tele-presence in which accurate distance judgments are

necessary. Although it seems likely that future VE technology will improve enough to

enable accurate distance judgments, a brief period of training with feedback may offer an

immediate and cost effective alternative.



The second question we investigated concerned the ability of the positive effect of

feedback to persist for at least 1 week after training. Our findings clearly show that the

level of improvement made immediately after feedback training was maintained over the

1-week intersession interval. The present finding thus puts a lower bound on the duration

of feedback’s positive effect. Of course, critical questions remain, such as, how long

individuals can remain at an accurate level of performance, and, when accuracy begins to

deteriorate, how much re-training will be necessary to bring performance back to accurate

levels?

An unexpected finding involved the effect of time and practice on exocentric distance

estimates in the no feedback group. It is clear from Figure 4 that exocentric distance

judgments from participants who received no feedback increased systematically through-

out the experiment—from nearly veridical (0.97) at pre-test, to overestimations imme-

diately after training (1.15) and 1 week later (1.22). This drift away from accuracy towards

overestimation of exocentric intervals was also recently illustrated and examined by

Philbeck, O’Leary, and Lew (2004), who suggested that the very act of blindfolded

walking influences the relationship between observers’ actions and the intended effects of

those actions. According to this hypothesis, when participants engage in blindfolded

walking, they become more accustomed to a situation in which their movements result in

diminished visual consequences. In essence, people learn that their movements have

reduced (or no) visual effects, and attempt to walk farther to achieve the typical visual

consequences of their movement. Of course, this hypothesis is not entirely satisfactory

because it does not explain why egocentric estimates were not similarly affected by

Feedback Group

Egocentric Exocentric None

Rel

ativ

eIm

prov

emen

t

-1.0

-0.5

0.0

0.5

1.0

1.5

EgocentricExocentric

Distance Judgment

Figure 6. Relative improvement (error bars represent one standard error) of distance estimates fromExperiment 1 as a function of type of distance and feedback group. Negative values indicateimpaired performance while positive values indicate improved performance (see text for description

of measure)



experience with blindfolded walking (see the white bars in Figure 4). Nonetheless, we find

it notable to have replicated this drift effect for larger exocentric intervals than those

examined by Philbeck et al. (2004), and regard our finding of no such effect for egocentric

distances as additional suggestive evidence that egocentric and exocentric distance

estimates are influenced by separable mental processes.

More direct evidence for a difference between egocentric and exocentric distance

estimates was illustrated by the final aim of this experiment—examining the effect of

feedback about egocentric (or exocentric) distances on judgments of exocentric (or

egocentric) distances. The results here were also unambiguous. Egocentric feedback

primarily improved egocentric estimates of distance, while exocentric feedback primarily

improved exocentric estimates of distance. This is a novel finding, and suggests that

exocentric distance judgments rely on more than judged egocentric relations. As we

mentioned in the introduction, our theoretical approach to understanding distance

estimates treats a perceived distance as the primary basis on which distance estimates

are made (although distance estimates can be further influenced by high-level non-

perceptual processes). Thus, one might speculate that exocentric distances are judged by

combining various egocentric percepts, such as perceived egocentric distances and angles.

Such a conceptualization of exocentric distance estimation would predict that interven-

tions affecting the perception of egocentric distances would have a related effect on

exocentric distance perception. That our data do not support this relation suggests that

perhaps the perception of these two types of distances involves separable mental

processes. However, an alternative explanation may be that feedback did not actually

alter the perception of egocentric distance, but only the subsequent mental processes that

influenced the observers’ specific responses to that distance. Determining if this was the

case was the primary motivation behind Experiment 2.

EXPERIMENT 2

In Experiment 2, we investigated the extent to which the effect of feedback found in

Experiment 1 generalizes to other means of indicating distances. This experiment also

enabled us to address the question of whether participants’ improvement as a result of

feedback training in Experiment 1 was due to a readjustment of their perception of

distance, or to a subsequent mental process that influenced their walking response. In

Experiment 2, we required participants to indicate distances in two ways: by direct

blindfolded walking, as in Experiment 1, and by indirect blindfolded walking (or

triangulation by walking). In the triangulation by walking procedure (see Fukusima,

Loomis, & Da Silva, 1997; Philbeck et al., 1997; Philbeck & Loomis, 1997), the observer

views a target and then, without vision, traverses a path that is oblique to the target. When

instructed, the observer turns to face the target and walks a few steps toward it. This

terminal heading is assumed to be in the direction of the initially perceived target location,

and an estimate of distance can be derived by combining the executed turns with the

walked distance via the law of sines. The triangulation by walking procedure in

combination with direct walking has been used by several researchers as a measure of

perceived distance (Fukusima et al., 1997; Loomis, Lippa, Klatzky, & Golledge, 2002;

Philbeck et al., 1997; Philbeck & Loomis, 1997).

In order to determine baseline performance on the tasks, participants made an initial

set of distance estimates by means of both direct and indirect blindfolded walking.



Participants then received feedback regarding only their estimates from the direct

blindfolded walking task. After this training, participants made estimates of a new set

of six distances by means of both direct and indirect blindfolded walking tasks. If feedback

training affects an observer’s percept of distance, performance on both direct and indirect

tasks should improve comparably after training. Thus, if performance on the indirect

walking task does not improve as much as direct walking as a result of feedback on the

direct walking task, we can conclude that feedback training does not affect the percept of

distance, but rather exerts its influence on at least one processing stage after perception.

Because feedback training principally affected judgments of egocentric distances in

Experiment 1, we focus exclusively on egocentric distance estimates in Experiment 2.

Method

Observers

Eighteen (nine male, nine female) individuals participated in the study. Their average age

was 20.27 years (SD¼ 2.05). All participants had normal or corrected to normal vision.

Individuals participated in the experiment in return for credit towards a requirement in

their introductory psychology course.

Stimuli and apparatus

The computer system used to display the VE and to record participants’ estimates was the

same as that described in Experiment 1. Because the task involved only egocentric

distance judgments, each trial contained only a single target post, modelled to be 100 cm

tall, placed directly in front of the observer on a textured ground plane at the beginning of

each trial. The computer script was also modified in order to integrate data regarding the

user’s orientation and position, which were used to derive distance estimates from the

indirect blindfolded walking trials.

Procedure

Instruction and training phase. This portion of the experiment was the same as described

in Experiment 1 with the exception of additionally training observers in how to give

estimates on the indirect blindfolded walking trials. In all phases of the experiment that

involved indirect blindfolded walking, the direction (left or right) and length (0.8 m or

1.2 m) of the oblique path was counterbalanced. The oblique path was always 40� away

from the direct path. For indirect blindfolded walking trials, after participants viewed the

target and were ready to give their response, the HMD projected an all black scene that

essentially blindfolded the participant. Participants then searched for a yellow ball in the

VE that floated at eye level and indicated the direction of the oblique path they would

travel. As soon as participants began walking on the oblique path, this ball disappeared.

When participants had walked a predetermined distance (either 0.8 m or 1.2 m) along the

oblique path, the HMD displayed a stop sign. Participants then stopped walking and turned

to face the target location. Once facing the target, they took a few small steps toward the

target to indicate their terminal heading to the target. Participants were provided with four

such practice trials.

Pre-test. A pre-test assessed the accuracy of the observers’ distance estimates in the

absence of formal training. This pre-test consisted of 36 (18 direct and 18 indirect

blindfolded walking trials, with three replications of each of the six distances, 75 cm,



125 cm, 225 cm, 300 cm, 325 cm, or 425 cm, for each response type) estimates of

egocentric distance. The order of response types (direct or indirect blindfolded walking)

was randomized for each participant within each phase of the experiment.

Feedback training. After the pre-test, observers received training on the direct blindfolded

walking task. Observers judged another set of 18 egocentric trials and, as in Experiment 1

were given feedback after each estimate.

Immediate post-test. After the feedback training, an immediate post-test was administered

to assess the effect of training. A new set of 36 trials (18 direct blindfolded walking and 18

indirect blindfolded walking) with novel target locations and new distances was presented

to the observers. The new distances to be judged in this phase of the experiment were

90 cm, 145 cm, 250 cm, 315 cm, 390 cm, and 410 cm.

Design

This experiment represents a 2 (phase: pre-training test vs. post-training test)� 2

(response type: direct blindfolded walking, indirect blindfolded walking) design, with

both factors manipulated within subjects. The main dependent variable used in the

following analyses was observers’ mean proportional error in judgment, defined as the

(judged distance/actual distance), collapsed over the six judged distances and three

replications of each distance. Parameter estimates are reported along with the width of

their associated 95% confidence intervals.

Results

As Figure 7 depicts, direct blindfolded walking estimates improved 42% (� 0.08) from

0.47 (� 0.07) in the pre-test to 0.89 (� 0.06) in the post-test, while indirect blindfolded

walking estimates improved only 13% (� 0.04) from 0.52 (� 0.05) in the pre-test to 0.65

(� 0.07) in the post-test after feedback training. A 2 (phase: pre-training test, post-training

test)� 2 (response type: blindfolded walking, triangulation) repeated measures ANOVA,

revealed a significant interaction between the factors of phase and response task,

confirming that estimates made from direct blindfolded walking improved significantly

more than estimates from the triangulation task after feedback training (F(1, 17)¼ 43.08,

MSE¼ 0.008, p< 0.01, f¼ 0.76).

Discussion

In Experiment 2, participants estimated distances by both direct and indirect blindfolded

walking, but were only given error-corrective feedback about their performance with

direct blindfolded walking. Before feedback training, distance judgments made by indirect

blindfolded walking were as accurate as those made by direct blindfolded walking. This

replicates previous work that has used indirect blindfolded walking as a measure of

perceived distance (Fukusima et al., 1997; Philbeck et al., 1997; Philbeck & Loomis,

1997) and suggests that, before training, distance judgments were based on a response-

independent percept of target location (see Loomis et al., 1996). If feedback training had

been able to alter this percept, we would have expected to find similar improvement in

both direct and indirect blindfolded walking distance estimates. However, feedback



training had a significant impact only on the specific response to which it was given—

direct blindfolded walking. Thus, the lack of similar improvement in indirect blindfolded

walking responses suggests that feedback training did not affect participants’ perception

of distance in the VE. In the General Discussion, we speculate on the mental processes that

are affected by feedback training.

Despite these conclusions, it is interesting to note that estimates made by indirect

blindfolded walking did improve slightly as a result of feedback. One possible reason for

the small increase in accuracy is that participants acquired a cognitive understanding of

their underestimation bias during the experiment, and attempted explicitly to readjust all

of their estimates. Alternatively, it is possible that participants’ percepts were partially

altered by training, and resulted in a partial change to their indirect estimates of distance.

Currently though, we feel that the better explanation is that indirect estimates were altered

as a result of cognitive influences. During the feedback training phase of the experiment,

observers were made aware that they had been underestimating distances. It seems natural

that they would thus modify their responses on both the direct and indirect trials. However,

because they received no feedback about their accuracy with indirect blindfolded walking,

they were less able to adjust these responses to the correct values. This hypothesis is

supported by post-experiment interviews, in which most participants expressed that they

were aware during training that they were underestimating distances and tried to adjust

their estimates accordingly.

Phase

Pre-Training Post-Training

Mea

nP

ropo

rtio

nalE

rror

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Veridical

Direct Blindfolded WalkingIndirect Blindfolded Walking

Response Type

Figure 7. Mean proportional error (error bars represent one standard error) in egocentric distanceestimates from Experiment 2, defined as (estimated distance/actual distance) a function of phase andtype of response. Values lower than 1 are indicative of underestimation and values above 1 indicate

overestimations



GENERAL DISCUSSION

A number of studies in the past decade have reliably established that in VEs, egocentric

distances between 1 and 25 m are estimated to be only 50 to 60% of the modelled distance

(J. M. Knapp, unpublished PhD dissertation, 1999; Loomis & Knapp, 2003; Thompson

et al., 2004; Witmer & Kline, 1998; Witmer & Sadowski, 1998). This is a limitation of

VEs that inhibits their effective use in many of their proposed applications. For example,

VEs that are used for training typically require trainees to learn spatial relationships in

the VE, and then to apply them in the real world (Bliss et al., 1997; Waller, Hunt, & Knapp,

1998). If the learned spatial relationships are biased, then performance on subsequent

transfer tasks that require accurate knowledge is likely to suffer. The current results

replicate the findings of other researchers showing that egocentric distance underestima-

tion in VEs is a real and significant problem.

More importantly, our results indicate that an effective—though limited—means of

improving distance estimation is with error-corrective feedback. This study has shown that

with a short period of feedback training, observers’ estimates of absolute egocentric (as

well as exocentric) distance can become accurate, and that this level of improvement can

last for at least 1 week. Feedback training thus can provide an immediate alternative to the

potentially costly improvements required to enhance VE technology.

An important practical question emerges from these findings: How much training is

necessary to improve performance? In our case, feedback training consisted of 5 to 10 min

of practice with the distance estimation task. However, because the results of Experiment 2

suggest that at least some of the effect of feedback operates at an explicit cognitive level, it

may be possible to produce valid estimation strategies with minimal intervention. For

example, an effective training method may be as simple as providing observers with the

statement that people tend to underestimate egocentric distance in VEs by about 50%. If

observers were able to use this one piece of information to improve their estimates, it

would be a positive step towards the development of walk-up-and-use VE systems, in

which lengthy training procedures may be impractical.

Despite the potential of feedback training, most of our work illustrates its limitations.

The effect of feedback in the current experiments was specific to both the type of judgment

and to the type of response. Thus, feedback about egocentric distances had only a small

effect (d¼ 0.28) on subsequent judgments of exocentric intervals, and feedback regarding

exocentric intervals had a small to moderate effect (d¼ 0.35) on subsequent judgments of

egocentric distances. Moreover, feedback about how to indicate egocentric distances

accurately did not transfer well to other means of indicating distances.

The inability of feedback’s effect to transfer to alternate distance estimation tasks

suggests that feedback does not affect a user’s percept of distance, but rather operates on

higher-level cognitive or response selection processes. Although perceptual learning (i.e.

the ability of people to pick up information from the environment differently as a result of

training) has been shown to operate as a result of exposure to photographic displays (see,

for example, Goldstone, Steyvers, Spencer-Smith, & Kersten, 2000; Redding & Wallace,

1997), we are unaware of any work that has shown perceptual learning as a result of VE

training. Likewise, our results suggest that feedback training modified not how users

perceived the distances to objects, but how they subsequently processed this percept.

Our results are consistent with the idea that the psychological processes affected by

feedback in these experiments involve explicit higher-level cognitive strategies for

estimating distance. If participants adopted a simple rule-based strategy such as ‘walk



half again as far as it really looks’ it would have been an effective means of increasing the

accuracy of their judgments for the specific situations in which they were given feedback.

Moreover, if participants attempted to generalize such a strategy to other situations, it may

explain why feedback was less effective in those situations. For example, in Experiment 1,

judgments of exocentric distances—which were generally veridical before training—

were subsequently overestimated as a result of feedback on egocentric distance judgments

(see the black bars in Figure 5). Similarly, as we noted in Experiment 2, performance on

the indirect blindfolded walking task was altered slightly (by 13%) as a result of feedback

on the direct walking task. In both of these cases, the obtained results can be explained by

assuming that participants had learned a rule such as ‘walk a little bit further than it

appears’ but did not know how to apply this rule in a new situation.

Our account of feedback’s effect as creating an explicit cognitive strategy differs from

previous explanations of its effect that regard it as involving a recalibration process

(Gibson & Bergman, 1954). Recalibration accounts of distance estimation describe a

retuning of the observer’s action/perception system, so that subsequent actions are

performed differently to achieve the same intended effects. While it may be possible to

regard the effect of feedback in our experiments as a type of recalibration, it is important to

note that typical recalibration studies have achieved their results by introducing dis-

crepancies among the available sources of sensory information during training (Mohler

et al., 2004; Rieser, Pick, Ashmead, & Garing, 1995; Welch, 1974). Participants can be

unaware of the effects of these discrepancies (see, for example, Rieser et al., 1995). By

contrast, in our experiments, the feedback we provided did not involve sensory rearrange-

ment. Moreover, our feedback was explicit, and most of our participants reported having a

clear awareness of its effect. For these reasons, we feel that the best way to characterize the

effect of feedback in our experiments is not as influencing a recalibration process, but

rather as effecting an explicit cognitive strategy. Of course, it is possible that less explicit

forms of feedback would have also enabled increased accuracy in distance judgments.

The idea of using less explicit forms of feedback has interesting implications for

alternative (and perhaps more flexible) ways of training distance estimation skills in VEs.

In the present experiment, accurate distance estimates were achieved by means of explicit

feedback about observers’ biased responses. However, it would be possible to convey this

feedback implicitly, by simply allowing observers to interact with the VE and to

experience the consequent violations of their expectations about distances. Thus, for

example, if an object that was 4 m from an observer appeared to be only 2 m away, this

appearance might subsequently be altered as a result of the realization that it requires 4 m

worth of walking to reach it. Presumably, this realization could occur as a result of normal

closed-loop experiences with the environment. Whether such experiences would serve to

recalibrate distance estimations, generate cognitive strategies for estimating distances, or

alter the perception of distance, or whether they would have negative aftereffects in the

real world are worthy topics for future research.

ACKNOWLEDGEMENTS

Adam Richardson, Department of Psychology, Miami University; David Waller, Depart-

ment of Psychology, Miami University.

We thank Len Mark, Marvin Dainoff, and Yvonne Lippa for their helpful comments on

earlier drafts.



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