Influence of the size of the field of view on motion perception

Pretto, Paolo; Ogier, M.; Bülthoff, HH; Bresciani, Jean‐Pierre

doi:10.1016/j.cag.2009.01.003

Cited by 47 publications

(61 citation statements)

References 23 publications

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“…The effects of the factor variables on vection ratings were consistent between the different path models. The specific findings were also mostly consistent with previous literature: It was found that a larger FOV increased vection ratings (Habak et al, 2002;Pretto et al, 2009) and that a ground-plane scene increases vection ratings over a dot cloud scene (Brandt et al, 1975;Nakamura & Shimojo, 1999;Riecke et al, 2006); for those participants who overestimated heading angle, a cosine-bell motion profile increased vection ratings compared to a constant velocity motion profile (Palmisano et al, 2008).…”

Section: Vectionsupporting

confidence: 90%

“…Peripheral vision, and therefore the size of the FOV, strongly affects vection (Habak, Casanova, & Faubert, 2002). Although FOVs of around 608 are sufficiently large to induce vection (Andersen & Braunstein, 1985;Pretto, Ogier, Bülthoff, & Bresciani, 2009), displays with larger FOVs or even floor projection improve vection nonetheless (Trutoiu, Streuber, Mohler, Schulte-Pelkum, & Bülthoff, 2008). Similarly, stereoscopic displays have been shown to induce more compelling vection (Palmisano, 1996(Palmisano, , 2002Ziegler & Roy, 1998).…”

Section: Vectionmentioning

confidence: 99%

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Effects of visual stimulus characteristics and individual differences in heading estimation

2018

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Visual heading estimation is subject to periodic patterns of constant (bias) and variable (noise) error. The nature of the errors, however, appears to differ between studies, showing underestimation in some, but overestimation in others. We investigated whether field of view (FOV), the availability of binocular disparity cues, motion profile, and visual scene layout can account for error characteristics, with a potential mediating effect of vection. Twenty participants (12 females) reported heading and rated vection for visual horizontal motion stimuli with headings ranging the full circle, while we systematically varied the above factors. Overall, the results show constant errors away from the fore-aft axis. Error magnitude was affected by FOV, disparity, and scene layout. Variable errors varied with heading angle, and depended on scene layout. Higher vection ratings were associated with smaller variable errors. Vection ratings depended on FOV, motion profile, and scene layout, with the highest ratings for a large FOV, cosine-bell velocity profile, and a ground plane scene rather than a dot cloud scene. Although the factors did affect error magnitude, differences in its direction were observed only between participants. We show that the observations are consistent with prior beliefs that headings align with the cardinal axes, where the attraction of each axis is an idiosyncratic property.

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Section: Vectionsupporting

confidence: 90%

Section: Vectionmentioning

confidence: 99%

Effects of visual stimulus characteristics and individual differences in heading estimation

2018

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“…These explanations, which suggest that the wider field of view (in this study, the three-screen condition) may affect hazard detection independently of the hazard location and of the availability of additional hazard-relevant information, receive some support from the main effect of screens and from the fact that most of the hazards had no hazard-relevant information in the side screens. In spite of this, it is possible that even where no hazard-relevant information whatsoever was available in the lateral screens, participants in the three-screen condition perceived higher speeds compared to participants in the single-screen condition (e.g., Alfano and Michel, 1990;Jamson, 2000;Pretto et al, 2009;Toet et al, 2007), resulting in higher levels of subjective risk perception in the same scenarios amongst participants in the three-screen condition. It is actually quite difficult to evaluate the extent to which the latter explanation could account for the group differences in this study.…”

Section: Resultsmentioning

confidence: 99%

“…It is actually quite difficult to evaluate the extent to which the latter explanation could account for the group differences in this study. Specifically, distortions in speed perception (typically decrements in speed estimations as a negative function of the size of visual field; Toet et al, 2007) appear to be restricted to (or at least more likely to occur in) relatively narrow visual angles (lower than 60 • ; Alfano and Michel, 1990;Pretto et al, 2009). In this study however, while the horizontal visual angle of the central screen was approximately 42 • wide (hence, a visual angle of less than 60 • for the single-screen condition), and this extended to 112 • when the side screens were included, the actual view of the forward cameras on the film car was however closer to 180 • , with the central 90 • within these 180 • displayed on the central screen (hence, a visual angle greater than 60 • for the single-screen condition).…”

Section: Resultsmentioning

confidence: 99%

Hazard perception as a function of target location and the field of view

Shahar¹,

Alberti²,

Clarke³

et al. 2010

Accident Analysis & Prevention

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“…The larger simulated field of view (the FOV used by the graphics generator to render its images) used in the third-person perspective, in combination with the reference provided by the avatar's head, helps users to more accurately estimate distances, and to better anticipate and extrapolate the speed and trajectory of vehicles (Salamin et al, 2006). A larger simulated FOV also allows the representation of more motion cues (vehicles) in the peripheral part of the display, thereby enhancing the perception of speed (Pretto, Ogier, Bülthoff, & Bresciani, 2009) and increasing perceived speed (Gogel & McNulty, 1983). The downward tilted viewing angle slightly increases the visual angle between objects, thereby increasing their perceived separations.…”

Section: Enhancements Of the Virtual Environmentmentioning

confidence: 99%

Visual and Auditory Cue Effects on Risk Assessment in a Highway Training Simulation

Toet¹,

Houtkamp

Meulen³

2013

Simulation & Gaming

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We investigated whether manipulation of visual and auditory depth and speed cues can affect a user's sense of risk for a low-cost nonimmersive virtual environment (VE) representing a highway environment with traffic incidents. The VE is currently used in an examination program to assess procedural knowledge of highway patrol officers. In its original form, the VE did not convey the danger of the simulated incidents, and trainees did not experience a sense of risk, even though important elements which contribute to a sense of danger in reality (like the speed and proximity of vehicles) were accurately modeled. This deficiency seriously degrades the validity of the VE as an examination tool. To provide viewers a more compelling impression of a simulated highway incident, we added variability to traffic behavior, and enhanced and added several visual and auditory depth and speed cues in the VE, which are known to affect risk perception in reality. Participants passively watched video clips of both the original and the enhanced versions of the simulation, and actively performed a lane crossing task in both interactive versions of the VE. Then, they filled out questionnaires addressing their speed, distance, and risk perception. The implemented changes did not affect speed and distance estimates, but significantly increased perceived personal risk. These results show that relatively minor changes to the visual, auditory, and dynamic aspects of a VE, established through proper analysis of user requirements and tasks, can significantly influence a user's experience, and thus determine the validity of the simulation for training and evaluation applications.

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Influence of the size of the field of view on motion perception

Cited by 47 publications

References 23 publications

Effects of visual stimulus characteristics and individual differences in heading estimation

Effects of visual stimulus characteristics and individual differences in heading estimation

Hazard perception as a function of target location and the field of view

Visual and Auditory Cue Effects on Risk Assessment in a Highway Training Simulation

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