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Cedric Goulon

dblp:31/8720 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1Human-computer interaction and ubiquitous computing · 1

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.

Human-computer interaction and pervasive computing
1 paper
Immersive interaction · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Immersive interaction › depth perception
distance perception
0.212015
Does virtual reality affect visual perception of egocentric distance? · VR 2015
Immersive interaction
virtual reality
0.212015
Does virtual reality affect visual perception of egocentric distance? · VR 2015
Immersive interaction › virtual reality
driving simulation
0.112015
Does virtual reality affect visual perception of egocentric distance? · VR 2015
YearPublicationVenuePosition
2015 Does virtual reality affect visual perception of egocentric distance?
abstract
Virtual reality (driving simulators) tends to generalize for the study of human behavior in mobility. It is thus crucial to ensure that perception of space and motion is little or not affected by the virtual environment (VE). The aim of this study was to determine a metrics of distance perception in VEs and whether this metrics depends on interactive factors: stereoscopy and motion parallax. After a training session, participants were asked, while driving, to estimate the relative location (5 to 80 m) of a car on the same road. The overall results suggest that distance perception in this range does not depend on interactive factors. In average, as generally reported, subjects underestimated the distances whatever the vision conditions. However, the study revealed a large interpersonal variability: two profiles of participants were defined, those who quite accurately perceived distances in VR and those who underestimated distances as usually reported. Overall, this classification was correlated to the level of performance of participants during the training phase. Furthermore, learning performance is predictive of the behavior of participants.
Thomas Rousset, Christophe Bourdin, Cedric Goulon, Jocelyn Monnoyer, Jean-Louis Vercher
VR3