An Analysis of the Motion Signal Distributions Emerging from Locomotion through a Natural Environment

Zanker, Johannes M.; Zeil, Jochen

doi:10.1007/3-540-36181-2_15

Cited by 5 publications

(5 citation statements)

References 36 publications

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“…Because there is a variation of local grating orientation, there always would be (spatially contiguous) regions that experience a 908 phase shift of the periodic patterns during the saccade öwhich naturally would create a strong motion signal in motion detectors receiving their input from those regions. This expected distribution of motion signals can easily be demonstrated by simulating a motion-detector network (cf Zanker 2001;Zanker and Zeil 2002). One recent computational study demonstrates that displacements of Riley patterns lead to characteristic motion-signal mapsöhorizontal streaks of motion signals in various directionsöwhich strongly resemble the perceived motion illusion (Zanker 2004).…”

Section: Discussionmentioning

confidence: 91%

Gaze Stability of Observers Watching Op Art Pictures

2003

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It has been the matter of some debate why we can experience vivid dynamic illusions when looking at static pictures composed from simple black and white patterns. The impression of illusory motion is particularly strong when viewing some of the works of 'Op Artists, such as Bridget Riley's painting Fall. Explanations of the illusory motion have ranged from retinal to cortical mechanisms, and an important role has been attributed to eye movements. To assess the possible contribution of eye movements to the illusory-motion percept we studied the strength of the illusion under different viewing conditions, and analysed the gaze stability of observers viewing the Riley painting and control patterns that do not produce the illusion. Whereas the illusion was reduced, but not abolished, when watching the painting through a pinhole, which reduces the effects of accommodation, it was not perceived in flash afterimages, suggesting an important role for eye movements in generating the illusion for this image. Recordings of eye movements revealed an abundance of small involuntary saccades when looking at the Riley pattern, despite the fact that gaze was kept within the dedicated fixation region. The frequency and particular characteristics of these rapid eye movements can vary considerably between different observers, but, although there was a tendency for gaze stability to deteriorate while viewing a Riley painting, there was no significant difference in saccade frequency between the stimulus and control patterns. Theoretical considerations indicate that such small image displacements can generate patterns of motion signals in a motion-detector network, which may serve as a simple and sufficient, but not necessarily exclusive, explanation for the illusion. Why such image displacements lead to perceptual results with a group of Op Art and similar patterns, but remain invisible for other stimuli, is discussed.

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Section: Discussionmentioning

confidence: 91%

Gaze Stability of Observers Watching Op Art Pictures

2003

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“…Since this change in motion direction defines the location of the poles, direction profiles can be used to compare motion signal maps generated in different scenes, by asking how clearly poles can be detected in the direction profiles (cf. Zanker & Zeil 2002). We restrict our analysis here to a mainly qualitative inspection of motion signal maps and discuss later some ways of assessing them quantitatively.…”

Section: Analysing Motion Signal Mapsmentioning

confidence: 99%

“…One way of assessing the quality of the information contained in the direction profiles is a very simple estimation procedure, which suggests that even sparse panoramic distributions are a very rich source of information (Zanker & Zeil 2002). The procedure is to fit a simple mathematical function to the data, which reflects the expectation of a basic directional profile.…”

Section: The Environment Emd-properties and Motion Signal Distributmentioning

confidence: 99%

Movement-induced motion signal distributions in outdoor scenes

Zanker

Zeil

2005

Network: Computation in Neural Systems

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The movement of an observer generates a characteristic field of velocity vectors on the retina (Gibson 1950). Because such optic flow-fields are useful for navigation, many theoretical, psychophysical and physiological studies have addressed the question how ego-motion parameters such as direction of heading can be estimated from optic flow. Little is known, however, about the structure of optic flow under natural conditions. To address this issue, we recorded sequences of panoramic images along accurately defined paths in a variety of outdoor locations and used these sequences as input to a two-dimensional array of correlation-based motion detectors (2DMD). We find that (a) motion signal distributions are sparse and noisy with respect to local motion directions; (b) motion signal distributions contain patches (motion streaks) which are systematically oriented along the principal flow-field directions; (c) motion signal distributions show a distinct, dorso-ventral topography, reflecting the distance anisotropy of terrestrial environments; (d) the spatiotemporal tuning of the local motion detector we used has little influence on the structure of motion signal distributions, at least for the range of conditions we tested; and (e) environmental motion is locally noisy throughout the visual field, with little spatial or temporal correlation; it can therefore be removed by temporal averaging and is largely over-ridden by image motion caused by observer movement. Our results suggest that spatial or temporal integration is important to retrieve reliable information on the local direction and size of motion vectors, because the structure of optic flow is clearly detectable in the temporal average of motion signal distributions. Ego-motion parameters can be reliably retrieved from such averaged distributions under a range of environmental conditions. These observations raise a number of questions about the role of specific environmental and computational constraints in the processing of natural optic flow.

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“…(1) Implementation in software, either on a PC (Zanker & Zeil 2002) or on a microcontroller (Ruffier et al 2003) (2) Implementation in (dedicated) digital, analogue, or hybrid hardware, either based on VLSI or aVLSI ASICs (Harrison 2000(Harrison , 2004(Harrison , 2005 or implemented with standard ICs (Franceschini et al 1992) (3) Implementation in configurable hardware like FPAA (Field Programmable Analogue Array, Ruffier et al 2003) or FPGA (Field Programmable Gate Array, Aubepart et al 2004, Zhang et al 2008 The first mentioned possibility has either the drawback of a high power consumption (PC) or does not have a suitable performance (microcontroller). The implementation in an ASIC, in contrast, can provide both a high performance and the best energy efficiency, but the drawback of an ASIC implementation is its reduced flexibility.…”

Section: Engineering Implementationsmentioning

confidence: 99%

Bio-inspired motion detection in an FPGA-based smart camera module

Köhler¹,

Röchter²,

Lindemann³

et al. 2009

Bioinspir. Biomim.

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Abstract. Flying insects, despite their relatively coarse vision and tiny nervous system, are capable of carrying out elegant and fast aerial manoeuvres. Studies of the fly visual system have shown that this is accomplished by the integration of signals from a large number of elementary motion detectors (EMDs) in just a few global flow detector cells. We developed an FPGA-based smart camera module with more than 10 000 single EMDs, which is closely modelled after insect motion-detection circuits with respect to overall architecture, resolution, and inter-receptor spacing. Input to the EMD array is provided by a CMOS camera with high frame rate. Designed as an adaptable solution for different engineering applications and as a testbed for biological models, the EMD detector type and parameters like the EMD time constants, the motion-detection directions, and the angle between correlated receptors are reconfigurable online. This allows a flexible and simultaneous detection of complex motion fields like translation, rotation and looming, such that various tasks e.g. obstacle avoidance, height/distance control, or speed regulation can be performed by the same compact device. Bio-inspired motion detection in an FPGA-based smart camera module2

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An Analysis of the Motion Signal Distributions Emerging from Locomotion through a Natural Environment

Cited by 5 publications

References 36 publications

Gaze Stability of Observers Watching Op Art Pictures

Gaze Stability of Observers Watching Op Art Pictures

Movement-induced motion signal distributions in outdoor scenes

Bio-inspired motion detection in an FPGA-based smart camera module

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