Ocular responses to radial optic flow and single accelerated targets in humans

Niemann, T.; Lappe, Markus; Büscher, Anja; Hoffmann, Klaus‐Peter

doi:10.1016/s0042-6989(98)00236-3

Cited by 41 publications

(42 citation statements)

References 46 publications

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“…This is consistent with the findings of Wilkie and Wann (2006) regarding OKN with very similar displays. The difference compared with the findings of Niemann et al (1999) might be attributed to the fact they used high-contrast black on white dots for their flow, whereas the flow here and in the study of Wilkie and Wann (2006) were homogenous textures lacking clear feature boundaries. In terms of adherence to the fixation requirement, the SD of the gaze position was 0.17°with a maximum excursion of 0.54°, and this showed little variation across the flow (SD gaze position, 0.16; maximum excursion, 0.50), road without flow (SD gaze position, 0.18; maximum excursion, 0.61), or road with flow (SD gaze position, 0.15; maximum excursion, 0.49) experimental conditions.…”

Section: Recorded Eye Movementscontrasting

confidence: 69%

“…This allowed us to ask whether fixation was equally efficient in the presence of the different visual stimuli, as well as to assess whether eye movement patterns differed between conditions when fixation was not enforced. Furthermore, the optic flow from the ground plane in many of the stimuli may have induced optokinetic nystagmus (OKN) (Niemann et al, 1999;Wilkie and Wann, 2006). Although control of OKN is normally attributed to subcortical areas, we wanted to establish whether OKN was present and ensure that there were no differences between experimental conditions.…”

Section: Experiments 2: Eye Movement Controlsmentioning

confidence: 99%

“…Niemann et al, 1999). We used Fourier analysis to estimate the spectral power attributable to OKN, and this accounted for only 2.9% of the power spectrum from 0 -10 Hz.…”

Section: Recorded Eye Movementsmentioning

confidence: 99%

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Neural Systems in the Visual Control of Steering

Field¹,

Wilkie²,

Wann³

2007

J. Neurosci.

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Visual control of locomotion is essential for most mammals and requires coordination between perceptual processes and action systems. Previous research on the neural systems engaged by self-motion has focused on heading perception, which is only one perceptual subcomponent. For effective steering, it is necessary to perceive an appropriate future path and then bring about the required change to heading. Using function magnetic resonance imaging in humans, we reveal a role for the parietal eye fields (PEFs) in directing spatially selective processes relating to future path information. A parietal area close to PEFs appears to be specialized for processing the future path information itself. Furthermore, a separate parietal area responds to visual position error signals, which occur when steering adjustments are imprecise. A network of three areas, the cerebellum, the supplementary eye fields, and dorsal premotor cortex, was found to be involved in generating appropriate motor responses for steering adjustments. This may reflect the demands of integrating visual inputs with the output response for the control device.

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Section: Recorded Eye Movementscontrasting

confidence: 69%

Section: Experiments 2: Eye Movement Controlsmentioning

confidence: 99%

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Neural Systems in the Visual Control of Steering

Field¹,

Wilkie²,

Wann³

2007

J. Neurosci.

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“…Without eye movements adapted to the speed of the optic flow, visual pick-up would be blurry. Therefore, a series of optokinetic eye movements is elicited (Solomon and Cohen, 1992;Lappe et al, 1998;Knapp et al, 2008;Niemann et al, 1999). This series of OKR's is called OptoKinetic Nystagmus (OKN) and has been described during simulated rectilinear self motion in the monkey and humans (Lappe et al, 1998;Niemann et al, 1999) and recently also during car driving (Authié and Mestre, 2011).…”

Section: Introductionmentioning

confidence: 99%

The visual control of bicycle steering: The effects of speed and path width

Vansteenkiste

Cardon

D’Hondt

et al. 2013

Accident Analysis & Prevention

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Although cycling is a widespread form of transportation, little is known about the visual behaviour of bicycle users. This study examined whether the visual behaviour of cyclists can be explained by the twolevel model of steering described for car driving, and how it is influenced by cycling speed and lane width. In addition, this study investigated whether travel fixations, described during walking, can also be found during a cycling task. Twelve adult participants were asked to cycle three fifteen meter long cycling lanes of 10, 25 and 40cm wide at three different self-selected speeds (i.e., slow, preferred and fast). Participants' gaze behaviour was recorded at 50Hz using a head mounted eye tracker and the resulting scene video with overlay gaze cursor was analyzed frame by frame. Four types of fixations were distinguished: (1) travel fixations, (2) fixations inside the cycling lane (path), (3) fixations to the final meter of the lane (goal), and (4) fixations outside of the cycling lane (external). Participants were found to mainly watch the path (41%) and goal (40%) region while very few travel fixations were made (<5%). Instead of travel fixations, an optokinetic nystagmus was revealed when looking at the near path. Large variability between subjects in fixation location suggests that different strategies were used. Wider lanes resulted in a shift of gaze towards the end of the lane and to external regions, whereas higher cycling speeds resulted in a more distant gaze behaviour and more travel fixations. To conclude, the two-level model of steering as described for car driving is not fully in line with our findings during cycling, but the assumption that both near and far regions are necessary for efficient steering seems valid. A new model for visual behaviour during goal directed locomotion is presented.

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“…Optic flow provides information about self-motion direction and results in eye movements to stabilize the perceived image on the retina [Niemann et al 1999]. An important feature of the optic flow is the focus of expansion (FoE).…”

Section: Related Workmentioning

confidence: 99%

Gaze behavior and visual attention model when turning in virtual environments

Hillaire

Lécuyer

Breton

et al. 2009

Proceedings of the 16th ACM Symposium on Virtual Reality Software and Technology

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In this paper we analyze and try to predict the gaze behavior of users navigating in virtual environments. We focus on first-person navigation in virtual environments which involves forward and backward motions on a ground-surface with turns toward the left or right. We found that gaze behavior in virtual reality, with input devices like mice and keyboards, is similar to the one observed in real life. Participants anticipated turns as in real life conditions, i.e. when they can actually move their body and head. We also found influences of visual occlusions and optic flow similar to the ones reported in existing literature on real navigations. Then, we propose three simple gaze prediction models taking as input: (1) the motion of the user as given by the rotation velocity of the camera on the yaw axis (considered here as the virtual heading direction), and/or (2) the optic flow on screen. These models were tested with data collected in various virtual environments. Results show that these models can significantly improve the prediction of gaze position on screen, especially when turning, in the virtual environment. The model based on rotation velocity of the camera seems to be the best trade-off between simplicity and efficiency. We suggest that these models could be used in several interactive applications using gaze point as input. They could also be used as a new top-down component in any existing visual attention model.

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Ocular responses to radial optic flow and single accelerated targets in humans

Cited by 41 publications

References 46 publications

Neural Systems in the Visual Control of Steering

Neural Systems in the Visual Control of Steering

The visual control of bicycle steering: The effects of speed and path width

Gaze behavior and visual attention model when turning in virtual environments

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