Perception of self-motion from visual flow

Lappe, Markus; Bremmer, Frank; Berg, Albert van den

doi:10.1016/s1364-6613(99)01364-9

Cited by 376 publications

(254 citation statements)

References 58 publications

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“…Of the visual cues available during locomotion, optic flow (see glossary) has been the most extensively investigated [3]. Optic flow cannot give information about absolute distance to an object and travel speed.…”

Section: Visual Cuesmentioning

confidence: 99%

“…Steering and vehicle speed control Heading Although optic flow is considered one of the most important types of visual information used for driving and for everyday locomotion [2,3], it can be ambiguous. Optic flow along the retina depends on eye and head movements [39] and different eye-head and body motion can produce very similar flow patterns.…”

Section: In Mathematical Terms Using a Simplified Version Of The Lonmentioning

confidence: 99%

“…In 1950 he described the visual perception of space [2] based on visual depth, distance or orientation stimulus variables. OPTIC FLOW, one of the most important visual cues he proposed, is defined as the visual motion experienced as a result of walking or driving, and it is thought to play a dominant role in the control of heading [3] and collision detection [4 -7]. However, regarding the control of the direction of movement in natural environments (i.e.…”

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confidence: 99%

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Evaluating perception in driving simulation experiments

Kemeny

Panerai

2003

Trends in Cognitive Sciences

280

147

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The use of driving simulation for vehicle design and driver perception studies is expanding rapidly. This is largely because simulation saves engineering time and costs, and can be used for studies of road and traffic safety. How applicable driving simulation is to the real world is unclear however, because analyses of perceptual criteria carried out in driving simulation experiments are controversial. On the one hand, recent data suggest that, in driving simulators with a large field of view, longitudinal speed can be estimated correctly from visual information. On the other hand, recent psychophysical studies have revealed an unexpectedly important contribution of vestibular cues in distance perception and steering, prompting a re-evaluation of the role of visuo-vestibular interaction in driving simulation studies.Vehicle driving implies perception and control of selfmotion at a greater range of velocities than locomotion by walking. It is often considered to be a task dominated by visual information. However, it is well-established that other sensory information, such as that provided by the vestibular and PROPRIOCEPTIVE (see Glossary) channels, also contributes to the perception and control of selfmotion. Motivated by a recent renewed interest in the role and function of these non-visual sensory modalities, we aim in this review to re-evaluate the role of visuovestibular interactions in driving simulation experiments, and to assess how applicable driving simulation is to the real world for studies of vehicle dynamics or driver behaviour.In 1938 Gibson [1] proposed a psychophysical theory of perception for automobile-driving, defining a 'terrain of field of space' for the driver, with the car considered as a tool of locomotion and the driver aiming to drive in the middle of a 'field of safe travel'. In 1950 he described the visual perception of space [2] based on visual depth, distance or orientation stimulus variables. OPTIC FLOW, one of the most important visual cues he proposed, is defined as the visual motion experienced as a result of walking or driving, and it is thought to play a dominant role in the control of heading [3] and collision detection [4 -7]. However, regarding the control of the direction of movement in natural environments (i.e. walking), there is still disagreement over whether the structure of the flow [8,9] or the visual EGOCENTRIC DIRECTION per se [10,11] is the dominant source of information. It is not clear either whether the same strategies used for natural locomotion apply to driving situations where displacements occur at higher velocities. Interestingly, a new point of view on these controversial issues was recently provided by experiments performed in driving simulators [12]. However, Gibson's original theory also included a definition of the perceptual field of the car itself, bringing to the driver kinaesthetic and tactile cues. These ideas were applied to driving simulation from the early 1980s [13][14][15], and since then many simulator experiments have been carried out for...

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Section: Visual Cuesmentioning

confidence: 99%

Section: In Mathematical Terms Using a Simplified Version Of The Lonmentioning

confidence: 99%

mentioning

confidence: 99%

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Evaluating perception in driving simulation experiments

Kemeny

Panerai

2003

Trends in Cognitive Sciences

280

147

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“…Explicit motion cues provide information about the relative position and movement of the perceiver and objects in the surrounding environment. In the visual modality, optic flow is responsible for providing this information which can be used to estimate both the velocity and direction of the self-motion [3]. Contrarily, implicit motion cues do not provide any information regarding the relative position and movement of the perceiver and the surrounding environment, but still suggest that movement may be occurring.…”

Section: Introductionmentioning

confidence: 99%

Vertical illusory self-motion through haptic stimulation of the feet

Nordahl

Nilsson

Turchet

et al. 2012

2012 IEEE VR Workshop on Perceptual Illusions in Virtual Environments

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Circular and linear self-motion illusions induced through visual and auditory stimuli have been studied rather extensively. While the ability of haptic stimuli to augment such illusions has been investigated, the self-motion illusions which primarily are induced by stimulation of the haptic modality remain relatively unexplored.In this paper, we present an experiment performed with the intention of investigating whether it is possible to use haptic stimulation of the main supporting areas of the feet to induce vertical illusory self-motion on behalf of unrestrained participants during exposure to a virtual environment depicting an elevator. The experiment was based on a within-subjects design where all participants were subjected to identical visual and auditory stimuli. The participants experienced a total of four conditions. For three of the conditions a different signal was used to generate the haptic feedback while the final condition included no haptic feedback. Analysis of self-reports were used to assess the participants' experience of illusory self-motion. The results indicate that such illusions are indeed possible. Significant differences were found between the condition including no haptic feedback and the remaining three conditions.

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“…The statistics of the true flow can be expected to show some homogeneity since a translational forward motion is dominant in the sequences that leads to a regular flow field (see, e.g., [26]). A detailed discussion of first order statistics of optic flow in natural scenes can be found in [5].…”

Section: Optic Flow Directionmentioning

confidence: 99%

Local image structures and optic flow estimation

Kalkan

Calow

Wörgötter

et al. 2005

Network: Computation in Neural Systems

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Abstract.Different kinds of local image structures (such as homogeneous, edge-like and junctionlike patches) can be distinguished by the intrinsic dimensionality of the local signals. Intrinsic dimensionality makes use of variance from a point and a line in spectral representation of the signal in order to classify it as homogeneous, edge-like or junction-like. The concept of intrinsic dimensionality has been mostly exercised using discrete formulations; however, a recent work [23,11] has introduced a continuous definition. The current study analyzes the distribution of local patches in natural images according to this continuous understanding of intrinsic dimensionality. This distribution reveals specific patterns than can be also associated to local image structures established in computer vision and which can be related to orientation and optic flow features. In particular, we link quantitative and qualitative properties of opticflow error estimates to these patterns. In this way, we also introduce a new tool for better analysis of optic flow algorithms.

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Perception of self-motion from visual flow

Cited by 376 publications

References 58 publications

Evaluating perception in driving simulation experiments

Evaluating perception in driving simulation experiments

Vertical illusory self-motion through haptic stimulation of the feet

Local image structures and optic flow estimation

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