Practical real-time imaging stereo matcher

Nishihara, H. K.

doi:10.1016/b978-0-08-051581-6.50013-1

Cited by 16 publications

(23 citation statements)

References 15 publications

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“…However, by introducing horizontal offsets between the random elements in some locations, the stimulus yields a percept of depth or depth structure when viewed stereoscopically. Importantly, these stimuli are remarkable because they demonstrate that disparity processing does not require monocularly identifiable elements or recognizable objects upon which to compute disparities; instead, the disparity extraction appears to be a low-level cross-correlation-like function, for which dense, random texture is, perhaps counterintuitively, actually the best input (Nishihara 1984). This implies an early extraction of disparities, likely at the point of initial binocular combination in primary visual cortex—as opposed to, say, after line segments are reconstructed in larger receptive fields or after a scene is parsed into meaningful elements.…”

Section: Introductionmentioning

confidence: 99%

Binocular Mechanisms of 3D Motion Processing

Cormack

Czuba

Knöll

et al. 2017

Annu. Rev. Vis. Sci.

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The visual system must recover important properties of the external environment if its host is to survive. Because the retinae are effectively two-dimensional but the world is three-dimensional (3D), the patterns of stimulation both within and across the eyes must be used to infer the distal stimulus—the environment—in all three dimensions. Moreover, animals and elements in the environment move, which means the input contains rich temporal information. Here, in addition to reviewing the literature, we discuss how and why prior work has focused on purported isolated systems (e.g., stereopsis) or cues (e.g., horizontal disparity) that do not necessarily map elegantly on to the computations and complex patterns of stimulation that arise when visual systems operate within the real world. We thus also introduce the binoptic flow field (BFF) as a description of the 3D motion information available in realistic environments, which can foster the use of ecologically valid yet well-controlled stimuli. Further, it can help clarify how future studies can more directly focus on the computations and stimulus properties the visual system might use to support perception and behavior in a dynamic 3D world.

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Section: Introductionmentioning

confidence: 99%

Binocular Mechanisms of 3D Motion Processing

Cormack

Czuba

Knöll

et al. 2017

Annu. Rev. Vis. Sci.

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“…In previous studies from this laboratory, relative response times were varied by either changing the spatial frequency of the stimuli (Gawne and Martin, 2002a; for references to the effects of spatial frequency on response latency see Marr and Poggio, 1979; Nishihara, 1984; Anderson and Van Essen, 1987; Parker et al, 1997; Bredfeldt and Ringach, 2002; Menz and Freeman, 2003; Frazor et al, 2004), or by changing the contrast and also the relative onset timing of the stimuli (Gawne, 2008). Evidence for rapid temporal gating was observed in these studies, where the temporal response to pairs of stimuli was completely dominated by the temporal response to the stimulus that by itself elicited the shortest latency.…”

Section: Discussionmentioning

confidence: 99%

Short-Time Scale Dynamics in the Responses to Multiple Stimuli in Visual Cortex

Gawne

2011

Front. Psychology

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Many previous studies have used the presentation of multiple stimuli in the receptive fields (RFs) of visual cortical neurons to explore how neurons might operate on multiple inputs. Most of these experiments have used two fixed stimulus locations within the RF of each neuron. Here the effects of using different positions within the RF of a neuron were explored. The stimuli were presented singly at one of six locations, and also at 15 pair-wise combinations, for 24 V2 cortical neurons in two macaque monkeys. There was considerable variability in how pairs of stimuli interacted within the receptive field of any given neuron: changing the position of the stimuli could result in enhancement, winner-take-all, or suppression relative to the strongest response to a stimulus presented by itself. Across the population of neurons there was no correlation between response strength and response latency. However, for many stimulus pairs the response latency was tightly locked to the shortest response latency of any single stimulus presented by itself independent of changes in response magnitude. In other words, a stimulus that by itself elicited a relatively long latency response, would often affect the magnitude of the response to a pair of stimuli, but not change the latency. These results may provide constraints on the development of models of cortical information processing.

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“…Assessing the tuning of these channels has been of great importance for mechanistic models of stereo computer vision (Marr and Poggio, 1979; Nishihara, 1984; Quam, 1987; Rohaly and Wilson, 1993). These can be used to map different scales of matching in hierarchical structures (Nishihara, 1984; Quam, 1987) with, for instance, coarse-to-fine constraints (Rohaly and Wilson, 1993).…”

Section: Introductionmentioning

confidence: 99%

“…These can be used to map different scales of matching in hierarchical structures (Nishihara, 1984; Quam, 1987) with, for instance, coarse-to-fine constraints (Rohaly and Wilson, 1993). In robotic vision, these tuning properties can be used to calibrate cameras (Tsai, 1986) and vergence algorithms (Piater et al, 1999; Lonini et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Characterization of Spatial Frequency Channels Underlying Disparity Sensitivity by Factor Analysis of Population Data

Reynaud

Hess

2017

Front. Comput. Neurosci.

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It has been suggested that at least two mechanisms mediate disparity processing, one for coarse and one for fine disparities. Here we analyze individual differences in our previously measured normative dataset on the disparity sensitivity as a function of spatial frequency of 61 observers to assess the tuning of the spatial frequency channels underlying disparity sensitivity for oblique corrugations (Reynaud et al., 2015). Inter-correlations and factor analysis of the population data revealed two spatial frequency channels for disparity sensitivity: one tuned to high spatial frequencies and one tuned to low spatial frequencies. Our results confirm that disparity is encoded by spatial frequency channels of different sensitivities tuned to different ranges of corrugation frequencies.

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Practical real-time imaging stereo matcher

Cited by 16 publications

References 15 publications

Binocular Mechanisms of 3D Motion Processing

Binocular Mechanisms of 3D Motion Processing

Short-Time Scale Dynamics in the Responses to Multiple Stimuli in Visual Cortex

Characterization of Spatial Frequency Channels Underlying Disparity Sensitivity by Factor Analysis of Population Data

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