2018
DOI: 10.1016/j.visres.2018.06.002
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The use of visual cues in gravity judgements on parabolic motion

Abstract: Evidence suggests that humans rely on an earth gravity prior for sensory-motor tasks like catching or reaching. Even under earth-discrepant conditions, this prior biases perception and action towards assuming a gravitational downwards acceleration of 9.81 m/s. This can be particularly detrimental in interactions with virtual environments employing earth-discrepant gravity conditions for their visual presentation. The present study thus investigates how well humans discriminate visually presented gravities and … Show more

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Cited by 14 publications
(23 citation statements)
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“…We restrict this comparison to the 0.7g/0.85g/1g/1.15/1.3g condition, as we expect 314 the gravity model not to be activated for inverted gravitational motion. For a discussion of factors 315 impacting the performance of the model for short occlusions, see (Jörges et al, 2018). We first simulate 316 a range of sensible standard deviations (from 0, corresponding to an impossibly precise representation, 317 to 0.28, corresponding to a quite imprecise representation with limited impact on the final percept, in 318 steps of 0.03) to determine the lower and upper bounds of the optimization interval (see Error!…”
mentioning
confidence: 99%
“…We restrict this comparison to the 0.7g/0.85g/1g/1.15/1.3g condition, as we expect 314 the gravity model not to be activated for inverted gravitational motion. For a discussion of factors 315 impacting the performance of the model for short occlusions, see (Jörges et al, 2018). We first simulate 316 a range of sensible standard deviations (from 0, corresponding to an impossibly precise representation, 317 to 0.28, corresponding to a quite imprecise representation with limited impact on the final percept, in 318 steps of 0.03) to determine the lower and upper bounds of the optimization interval (see Error!…”
mentioning
confidence: 99%
“…Smith et al (2018) showed that the extrapolation of ballistic pendulum motion is idiosyncratic and erroneous when people draw the trajectories, but consistent with accurate physical inferences under uncertainty when people must process pendulum trajectories to catch a ball or they release a pendulum to hit a target. Also, when observers were asked to judge which of two visually presented parabolic motions of a virtual target presented against a blank background had the higher simulated gravity, they generally showed high discrimination thresholds, suggesting that a prior of Earth gravity does not give rise to a discriminability of different gravity accelerations better than that for other arbitrary accelerations (Jörges et al, 2018).…”
Section: Introductionmentioning
confidence: 96%
“…For instance, humans should be able to detect minimal departures from veridical gravitational acceleration in visual scenes. However, the evidence that this is the case remains controversial Ceccarelli et al, 2018;Jörges et al, 2018;Vicovaro et al, 2019). The issue is especially relevant in rehabilitation applications requiring visuomotor interactions of the patients with the virtual reality setup.…”
Section: Introductionmentioning
confidence: 99%
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“…There is a growing corpus of research indicating that humans use their knowledge of earth gravity in a broad range of tasks, such as grasping (Verheij, Brenner, & Smeets, 2013), catching and interception (Bosco, Delle Monache, & Lacquaniti, 2012;Jörges, Hagenfeld, & López-Moliner, 2018;Lacquaniti et al, 2013;McIntyre, Zago, & Berthoz, 2001;McIntyre, Zago, Berthoz, & Lacquaniti, 2003;Senot, Zago, Lacquaniti, & McIntyre, 2005;Senot et al, 2012;Zago et al, 2004;Zago, McIntyre, Senot, & Lacquaniti, 2009;, duration estimation (Moscatelli & Lacquaniti, 2011) or the perception of biological motion (Jokisch & Troje, 2003;Maffei et al, 2015;Simion, Regolin, & Bulf, 2008), while arbitrary accelerations are generally neglected (Benguigui & Bennett, 2010;Benguigui, Ripoll, & Broderick, 2003) or used insufficiently. Here we examined ocular pursuit and spatial estimation in a linear prediction motion task that emphasized extrapolation of occluded accelerative object motion.…”
Section: Introductionmentioning
confidence: 99%