Catching a gently thrown ball

López‐Moliner, Joan; Brenner, Eli; Louw, S.; Smeets, Jeroen B. J.

doi:10.1007/s00221-010-2421-1

Cited by 46 publications

(52 citation statements)

References 21 publications

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“…The estimated individual delays ranged from 0.193 and 0.217 s for all the subjects. As these figures can be interpreted as the time between the moment when the optical information crosses a threshold and the initiation of action, the reported values are consistent with sensorio-motor delays estimated in similar tasks [26].…”

Section: Resultssupporting

confidence: 86%

“…The fact that people move more rapidly when intercepting fast objects [25] suggest an interplay between sensory and motor phases with possible overlapping periods of sensory information acquisition and motor action. The longer one sees a ball's trajectory the lower the error in predicting future positions but always leaving room to perform the action [26]. How the total time is allocated for perception and action reflects knowledge of sensory and movement uncertainty [27].…”

Section: Introductionmentioning

confidence: 99%

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People Favour Imperfect Catching by Assuming a Stable World

López‐Moliner

Keil

2012

PLoS ONE

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The visual angle that is projected by an object (e.g. a ball) on the retina depends on the object's size and distance. Without further information, however, the visual angle is ambiguous with respect to size and distance, because equal visual angles can be obtained from a big ball at a longer distance and a smaller one at a correspondingly shorter distance. Failure to recover the true 3D structure of the object (e.g. a ball's physical size) causing the ambiguous retinal image can lead to a timing error when catching the ball. Two opposing views are currently prevailing on how people resolve this ambiguity when estimating time to contact. One explanation challenges any inference about what causes the retinal image (i.e. the necessity to recover this 3D structure), and instead favors a direct analysis of optic flow. In contrast, the second view suggests that action timing could be rather based on obtaining an estimate of the 3D structure of the scene. With the latter, systematic errors will be predicted if our inference of the 3D structure fails to reveal the underlying cause of the retinal image. Here we show that hand closure in catching virtual balls is triggered by visual angle, using an assumption of a constant ball size. As a consequence of this assumption, hand closure starts when the ball is at similar distance across trials. From that distance on, the remaining arrival time, therefore, depends on ball's speed. In order to time the catch successfully, closing time was coupled with ball's speed during the motor phase. This strategy led to an increased precision in catching but at the cost of committing systematic errors.

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Section: Resultssupporting

confidence: 86%

Section: Introductionmentioning

confidence: 99%

People Favour Imperfect Catching by Assuming a Stable World

López‐Moliner

Keil

2012

PLoS ONE

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“…An apparent exception is a study of catching by López-Moliner, Brenner, Louw, and Smeets (2010), in which balls were repeatedly tossed from a distance of 75 cm, with a mean flight time of 483 ms, and randomly occluded for 250ms. Occlusion did not affect the “quality” of the catch, as long as the ball's motion was visible at release or 400-200 ms before the catch.…”

Section: Model-based Control: Is An Internal Model Sufficient?mentioning

confidence: 99%

“…A mapping is a quantitative correlation between optical variables and action variables or goal-states that can be used to guide behavior. As an example, recall López-Moliner et al's (2010) observation that, when tossing a ball back and forth, random occlusion did not affect catching if the ball was visible at release. The authors conclude that catching is normally continuously controlled, but can be guided by the ball's initial motion if the trajectory is occluded.…”

Section: Anticipatory Control Of Interceptive Action: Is An Internmentioning

confidence: 99%

On-line and model-based approaches to the visual control of action

2015

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Two general approaches to the visual control of action have emerged in last few decades, known as the on-line and model-based approaches. The key difference between them is whether action is controlled by current visual information or on the basis of an internal world model. In this paper, we evaluate three hypotheses: strong on-line control, strong model-based control, and a hybrid solution that combines on-line control with weak off-line strategies. We review experimental research on the control of locomotion and manual actions, which indicates that (a) an internal world model is neither sufficient nor necessary to control action at normal levels of performance; (b) current visual information is necessary and sufficient to control action at normal levels; and (c) under certain conditions (e.g. occlusion) action is controlled by less accurate, simple strategies such as heuristics, visual-motor mappings, or spatial memory. We conclude that the strong model-based hypothesis is not sustainable. Action is normally controlled on-line when current information is available, consistent with the strong on-line control hypothesis. In exceptional circumstances, action is controlled by weak, context-specific, off-line strategies. This hybrid solution is comprehensive, parsimonious, and able to account for a variety of tasks under a range of visual conditions.

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“…Nevertheless parabolic trajectories have been objects of attention in several studies that have examined how catching performance depends on vision of different parts of the parabolic path (e.g., Sharp and Whiting, 1974, 1975; Whiting and Sharp, 1974; Dessing et al, 2009; López-Moliner et al, 2010) or which visual information in fly balls is used to predict the landing point (Chapman, 1968; Oudejans et al, 1997; McLeod et al, 2003; Brouwer et al, 2006; Fink et al, 2009). However, putting forward a computational model that specifies how humans can time the parabolic catch has remained elusive.…”

Section: Introductionmentioning

confidence: 99%

Synergies between optical and physical variables in intercepting parabolic targets

Gómez¹,

López‐Moliner²

2013

Front. Behav. Neurosci.

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Interception requires precise estimation of time-to-contact (TTC) information. A long-standing view posits that all relevant information for extracting TTC is available in the angular variables, which result from the projection of distal objects onto the retina. The different timing models rooted in this tradition have consequently relied on combining visual angle and its rate of expansion in different ways with tau being the most well-known solution for TTC. The generalization of these models to timing parabolic trajectories is not straightforward. For example, these different combinations rely on isotropic expansion and usually assume first-order information only, neglecting acceleration. As a consequence no optical formulations have been put forward so far to specify TTC of parabolic targets with enough accuracy. It is only recently that context-dependent physical variables have been shown to play an important role in TTC estimation. Known physical size and gravity can adequately explain observed data of linear and free-falling trajectories, respectively. Yet, a full timing model for specifying parabolic TTC has remained elusive. We here derive two formulations that specify TTC for parabolic ball trajectories. The first specification extends previous models in which known size is combined with thresholding visual angle or its rate of expansion to the case of fly balls. To efficiently use this model, observers need to recover the 3D radial velocity component of the trajectory which conveys the isotropic expansion. The second one uses knowledge of size and gravity combined with ball visual angle and elevation angle. Taking into account the noise due to sensory measurements, we simulate the expected performance of these models in terms of accuracy and precision. While the model that combines expansion information and size knowledge is more efficient during the late trajectory, the second one is shown to be efficient along all the flight.

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Catching a gently thrown ball

Cited by 46 publications

References 21 publications

People Favour Imperfect Catching by Assuming a Stable World

People Favour Imperfect Catching by Assuming a Stable World

On-line and model-based approaches to the visual control of action

Synergies between optical and physical variables in intercepting parabolic targets

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