The Perception of Walking Speed in a Virtual Environment

Banton, Tom; Stefanucci, Jeanine K.; Durgin, Frank H.; Fass, Adam; Proffítt, Dennis R.

doi:10.1162/105474605774785262

Cited by 138 publications

(100 citation statements)

References 26 publications

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“…The scene matching task results show that subjects mostly underestimated the speed of the moving scene, regardless of mode. According to Banton et al [2005], the underestimation is due to inadequate laminar flow, which may account for some of our results. However, Durgin et al [2005a] found that these visual field speed judgments do not just depend on visual input, but also on self-motion of the subject, e.g., whether the subject was walking on a treadmill.…”

Section: Scene Speed Underestimationmentioning

confidence: 77%

A feedback-controlled interface for treadmill locomotion in virtual environments

Lichtenstein

Barabas

Woods

et al. 2007

ACM Trans. Appl. Percept.

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Virtual environments (VEs) allow safe, repeatable, and controlled evaluations of obstacle avoidance and navigation performance of people with visual impairments using visual aids. Proper simulation of mobility in a VE requires an interface, which allows subjects to set their walking pace. Using conventional treadmills, the subject can change their walking speed by pushing the tread with their feet, while leveraging handrails or ropes (self-propelled mode). We developed a feedback-controlled locomotion interface that allows the VE workstation to control the speed of the treadmill, based on the position of the user. The position and speed information is also used to implement automated safety measures, so that the treadmill can be halted in case of erratic behavior. We compared the feedback-controlled mode to the self-propelled mode by using speed-matching tasks (follow a moving object or match the speed of an independently moving scene) to measure the efficacy of each mode in maintaining constant subject position, subject control of the treadmill, and subject pulse rates. Additionally, we measured the perception of speed in the VE on each mode. The feedbackcontrolled mode required less physical exertion than self-propelled. The average position of subjects on the feedback-controlled treadmill was always within a centimeter of the desired position. There was a smaller standard deviation in subject position when using the self-propelled mode than when using the feedback-controlled mode, but the difference averaged less than six centimeters across all subjects walking at a constant speed. Although all subjects underestimated the speed of an independently moving scene at higher speeds, their estimates were more accurate when using the feedback-controlled treadmill than the self-propelled.

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Section: Scene Speed Underestimationmentioning

confidence: 77%

A feedback-controlled interface for treadmill locomotion in virtual environments

Lichtenstein

Barabas

Woods

et al. 2007

ACM Trans. Appl. Percept.

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“…Several studies using virtual environments and Head-Mounted Displays (HMD) revealed a distance compression effect [20,23,43], partially explained by the reduced field of view and the weight and the torques exerted by the HMD on the user's head. Similarly, the perceived velocity in a VR environment differs from the real locomotion velocity [2], introducing an additional bias. Other factors, such as the image contrast [13] and the point of view [25], also influence navigation efficiency in VR.…”

Section: Perception Of Self Locomotionmentioning

confidence: 99%

Kinematic Evaluation of Virtual Walking Trajectories

Cirio

Olivier

Marchal

et al. 2013

IEEE Trans. Visual. Comput. Graphics

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Fig. 1. The objective of this paper is to evaluate various virtual locomotion conditions by comparing reference with virtual trajectories formed during goal-directed locomotion tasks. Reference trajectories (left) can be recorded through motion capture or be generated through a numerical model of human locomotion. The paper demonstrates the framework (center) over a set of experimental trajectories (right). For the purpose of demonstration, this paper compares frequently used virtual locomotion conditions. Abstract-Virtual walking, a fundamental task in Virtual Reality (VR), is greatly influenced by the locomotion interface being used, by the specificities of input and output devices, and by the way the virtual environment is represented. No matter how virtual walking is controlled, the generation of realistic virtual trajectories is absolutely required for some applications, especially those dedicated to the study of walking behaviors in VR, navigation through virtual places for architecture, rehabilitation and training. Previous studies focused on evaluating the realism of locomotion trajectories have mostly considered the result of the locomotion task (efficiency, accuracy) and its subjective perception (presence, cybersickness). Few focused on the locomotion trajectory itself, but in situation of geometrically constrained task. In this paper, we study the realism of unconstrained trajectories produced during virtual walking by addressing the following question: did the user reach his destination by virtually walking along a trajectory he would have followed in similar real conditions? To this end, we propose a comprehensive evaluation framework consisting on a set of trajectographical criteria and a locomotion model to generate reference trajectories. We consider a simple locomotion task where users walk between two oriented points in space. The travel path is analyzed both geometrically and temporally in comparison to simulated reference trajectories. In addition, we demonstrate the framework over a user study which considered an initial set of common and frequent virtual walking conditions, namely different input devices, output display devices, control laws, and visualization modalities. The study provides insight into the relative contributions of each condition to the overall realism of the resulting virtual trajectories.

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“…1 Banton et al, (2005) determined that with an HMD, straight-ahead optic flow is perceived to be slower than an equivalent walking speed on the treadmill; a camera speed of 4.7 mph was used in the current experiment because it best matched a treadmill walking speed of 3 mph. Fig.…”

Section: Resultsmentioning

confidence: 99%

“…3). The VE was the same as that used in a previous treadmill study that investigated the perception of walking speed in a virtual environment (for specific details on the VE, see Banton, Stefanucci, Durgin, Fass, & Proffitt, 2005; newer hardware was used, and the golf cart was not shown). As participants walked on the treadmill, the virtual camera moved through the VE at a speed that had been determined previously to match perceived speed to the treadmill speed.…”

Section: Stimulimentioning

confidence: 99%

Optic flow is calibrated to walking effort

Zadra

Proffítt

2016

Psychon Bull Rev

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Through experience, people learn that a given magnitude of walking produces an associated magnitude of optic flow. Artificially altering this relationship has both behavioral and perceptual consequences: walking on a treadmill results in zero translational optic flow and causes people to subsequently drift forward when attempting to walk in place while blindfolded (they have learned that forward walking is required to remain stationary). Similarly, after walking on a treadmill people perceive the walking distance to targets to be greater (they have recalibrated the magnitude of walking required to reach the target). While the measurement unit for walking magnitude in this relationship has been treated as walking speed (stride length * [steps / time]), recent experiments suggest that walkable distances may instead be measured in bioenergetic units (i.e., the magnitude of energy required to produce a given magnitude of optic flow). In the first experiment, zero translational optic flow was paired with a constant walking speed, and walking energy was manipulated by varying the incline of the treadmill. Participants who walked on an inclined treadmill drifted farther while attempting to walk in place than participants who walked on a flat treadmill. A follow-up experiment presented optic flow via an immersive virtual environment, and no difference between flat and inclined treadmill walking was found, thereby showing that the effect found in the first experiment was not an artifact of biomechanical differences associated with flat versus inclined treadmill walking. The results support the hypothesis that walking magnitude is scaled by bioenergetic units. Keywords Embodied cognition . Perceptual learning . Physiological psychology . Visual . PerceptionThe current study investigated the visual-motor recalibration process responsible for updating the associative relationship between walking and optic flow. Walking produces optic flow, which consists of environment-specifying changes in visual angles. Moreover, as people walk they discover the relationship between the magnitudes of optic flow that are produced by varying magnitudes of walking. The current study investigated the effective variables specifying walking magnitude. More precisely, our research question in this context of visual-motor recalibration was: What is the measurement unit for walking magnitude?A number of studies have used a treadmill to investigate the relationship between walking and the visual information that accompanies it. Normally, optic flow is coupled to walking, such that walking at 3 mph produces 3 mph of optic flow. On a treadmill, regardless of walking or running speed, there is no translational optic flow. A number of experiments have shown that decoupling rate of walking from rate of optic flow has perceptual and behavioral effects, and anyone who has walked or run on a treadmill has experienced one of these: upon dismounting the treadmill one gets the strange feeling for a short while of moving too quickly when walking (Pela...

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The Perception of Walking Speed in a Virtual Environment

Cited by 138 publications

References 26 publications

A feedback-controlled interface for treadmill locomotion in virtual environments

A feedback-controlled interface for treadmill locomotion in virtual environments

Kinematic Evaluation of Virtual Walking Trajectories

Optic flow is calibrated to walking effort

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