Weighted directional energy model of human stereo correspondence

Prince, Simon J. D.; Eagle, Richard A

doi:10.1016/s0042-6989(99)00241-2

Cited by 44 publications

(39 citation statements)

References 49 publications

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“…At each disparity value the populations were tested with 40 stimuli (20 positive and 20 negative disparities). Open triangles depict performance for 0.8 cycles/ deg Nyquist frequency, solid triangles depict performance for 3.0 cycles/deg Nyquist frequency to linear combinations (Fleet et al 1996;Qian and Zhu 1997;Prince and Eagle 2000b). By contrast, information contained in a population response was extracted with an optimal and unbiased maximum-likelihood estimator (Oram et al 1998).…”

Section: Discussionmentioning

confidence: 99%

“…DeAngelis et al (1998) demonstrated that stimulation in area MT influences depth perception in the macaque monkey. In a theoretical study, Prince and Eagle (2000b) investigated the performance of a physiologically motivated model under several psychophysical tasks. They found effects formerly attributed to a postulated but yet unknown second nonlinear stereochannel and could thereby partly reconcile properties of the neurons with psychophysical data.…”

Section: Introductionmentioning

confidence: 99%

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Visual depth encoding in populations of neurons with localized receptive fields

Lippert¹,

Wagner²

2002

Biological Cybernetics

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Stereopsis is the ability to perceive three-dimensional structure from disparities between the two-dimensional retinal images. Although disparity-sensitive neurons have been proposed as a neural representation of this ability many years ago, it is still difficult to link all qualities of stereopsis to properties of the neural correlate of binocular disparities. The present study wants to support efforts directed at closing the gap between electrophysiology and psychophysics. Populations of disparity-sensitive neurons in V1 were simulated using the energy-neuron model. Responses to different types of stimuli were evaluated with an efficient statistical estimator and related to psychophysical findings. The representation of disparity in simulated population responses appeared to be very robust. Small populations allowed good depth discrimination. Two types of energy neurons (phase- and position-type models) that are discussed as possible neural implementations of disparity-selectivity could be compared to each other. Phase-type coding was more robust and could explain a tendency towards zero disparity in degenerated stimuli and, for high-pass stimuli, exhibited the breakdown of disparity discrimination at a maximum disparity value. Contrast-inverted stereograms led to high variances in disparity representation, which is a possible explanation of the absence of depth percepts in large contrast-inverted stimuli. Our study suggests that nonlocal interactions destroy depth percepts in large contrast-inverted stereograms, although these percepts occur for smaller stimuli of the same class.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Visual depth encoding in populations of neurons with localized receptive fields

Lippert¹,

Wagner²

2002

Biological Cybernetics

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“…There are several ways in which the output of the energy model may contribute to the estimation of disparity (see Fleet et al 1996b;Prince and Eagle 2000). Because the calculation is performed over a limited area (the RF), there will always be circumstances in which false matches can produce substantial correlations.…”

Section: What Do Disparity-selective Cells In V1 Calculate?mentioning

confidence: 99%

“…This has been used widely (e.g., Fleet et al 1996a,b;Prince and Eagle 2000;Qian 1994;Qian and Zhu 1997) since its inception and will be referred to here as "Gabor energy model." All experimental data used to assess its validity (Anzai et al 1999a(Anzai et al ,b, 1997DeAngelis et al 1995;Ohzawa and Freeman 1986a,b;Ohzawa et al 1990Ohzawa et al , 1996Ohzawa et al , 1997 have been gathered from V1 neurons in the anesthetized cat using one-dimensional stimuli (bars or gratings).…”

Section: Introductionmentioning

confidence: 99%

Quantitative Analysis of the Responses of V1 Neurons to Horizontal Disparity in Dynamic Random-Dot Stereograms

Prince

Pointon

Cumming

et al. 2002

Journal of Neurophysiology

209

238

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Quantitative analysis of the responses of V1 neurons to horizontal disparity in dynamic random-dot stereograms. J Neurophysiol 87: 191-208, 2002; 10.1152/jn.00465.2000. Horizontal disparity tuning for dynamic random-dot stereograms was investigated for a large population of neurons (n ϭ 787) in V1 of the awake macaque. Disparity sensitivity was quantified using a measure of the discriminability of the maximum and minimum points on the disparity tuning curve. This measure and others revealed a continuum of selectivity rather than separate populations of disparity-and nondisparity-sensitive neurons. Although disparity sensitivity was correlated with the degree of direction tuning, it was not correlated with other significant neuronal properties, including preferred orientation and ocular dominance. In accordance with the Gabor energy model, tuning curves for horizontal disparity were adequately described by Gabor functions when the neuron's orientation preference was near vertical. For neurons with orientation preferences near to horizontal, a Gaussian function was more frequently sufficient. The spatial frequency of the Gabor function that described the disparity tuning was weakly correlated with measurements of the spatial frequency and orientation preference of the neuron for drifting sinusoidal gratings. Energy models make several predictions about the relationship between the response rates to monocular and binocular dot patterns. Few of the predictions were fulfilled exactly, although the observations can be reconciled with the energy model by simple modifications. These same modifications also provide an account of the observed continuum in strength of disparity selectivity. A weak correlation between the disparity sensitivity of simultaneously recorded single-and multiunit data were revealed as well as a weak tendency to show similar disparity preferences. This is compatible with a degree of local clustering for disparity sensitivity in V1, although this is much weaker than that reported in area MT. I N T R O D U C T I O NSelectivity for binocular disparity was initially demonstrated using elongated bar stimuli in cat area 17 (Barlow et al. 1967;Pettigrew et al. 1968) and V1 of the awake monkey (Poggio and Fischer 1977). Subsequently, Poggio and colleagues (Poggio 1995;Poggio et al. 1985Poggio et al. , 1988 examined the sensitivity to horizontal disparity in random-dot stereograms (RDS) in macaque V1. None of the studies using RDS has attempted to describe the disparity tuning quantitatively. Consequently, there has been no quantitative analysis of the relationship between disparity selectivity to RDS and other fundamental properties of V1 neurons, such as orientation tuning and ocular dominance.There are several reasons why it is important to study these issues with RDS. First, a change in the disparity of a bar stimulus also generates changes in the monocular images, which by themselves may influence neuronal firing. By contrast the monocular images of random-dot stimuli are spatially homogeneous. There...

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“…Although several physiologically-based models have been proposed (Fleet et al, 1996;Grossberg, 1994;Grossberg and Howe, 2003;Lehky and Sejnowski, 1990;Lippert and Wagner, 2002;Matthews et al, 2003;McLoughlin and Grossberg, 1998;Mikaelian and Qian, 2000;Prince and Eagle, 2000;Qian, 1994Qian, , 1997Qian and Andersen, 1997;Read, 2002a,b;Tsai and Victor, 2003;Watanabe and Idesawa, 2003;Zhaoping, 2002), much work remains to be done in tying these theories more closely to the known physiology, and expanding them to provide a complete account of stereoscopic perception.…”

Section: Outstanding Questionsmentioning

confidence: 99%

Early computational processing in binocular vision and depth perception

Read

2005

Progress in Biophysics and Molecular Biology

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Stereoscopic depth perception is a fascinating ability in its own right and also a useful model of perception. In recent years, considerable progress has been made in understanding the early cortical circuitry underlying this ability. Inputs from left and right eyes are first combined in primary visual cortex (V1), where many cells are tuned for binocular disparity. Although the observation of disparity tuning in V1, combined with psychophysical evidence that stereopsis must occur early in visual processing, led to initial suggestions that V1 was the neural correlate of stereoscopic depth perception, more recent work indicates that this must occur in higher visual areas. The firing of cells in V1 appears to depend relatively simply on the visual stimuli within local receptive fields in each retina, whereas the perception of depth reflects global properties of the stimulus. However, V1 neurons appear to be specialized in a number of respects to encode ecologically relevant binocular disparities. This suggests that they carry out essential preprocessing underlying stereoscopic depth perception in higher areas. This article reviews recent progress in developing accurate models of the computations carried out by these neurons. We seem close to achieving a mathematical description of the initial stages of the brain's stereo algorithm. This is important in itself--for instance, it may enable improved stereopsis in computer vision--and paves the way for a full understanding of how depth perception arises. Stereopsis as a model of perceptionAlthough we have two eyes, we are not aware of the fact during visual perception: we perceive the world as if through a single "cyclopean eye" in the middle of our forehead. Yet at the same time, we have the remarkable ability to deduce depth from the small differences in left-and right-eye retinal images which occur because our eyes are set apart in our head. This stereoscopic ability and its counterpart, binocular single vision, have fascinated us since their existence was first fully appreciated in the nineteenth century. Recently, binocular vision has come into prominence as a tool for probing one of the fundamental questions of neuroscience: how external stimuli give rise to conscious perception.There are several reasons why stereopsis is a particularly suitable model system for this goal.1. The problem to be solved is relatively well-defined, compared to for example face or speech recognition, and its mathematical basis is thoroughly understood (Fig. 1;Hartley and Zisserman, 2000;Longuet-Higgins, 1981). 2.As a consequence of this simplicity, stereopsis can be studied in both animals and humans. Monkeys perceive stereoscopic depth much as humans do, and can be trained to report their perceptions (Bough, 1970). Thus, psychophysical studies of perception can be combined with electrophysiological studies of neuronal activity in the same animal--of critical importance in the attempt to relate perception and neuronal activity. 3.The circuitry specific to this task probably oc...

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Weighted directional energy model of human stereo correspondence

Cited by 44 publications

References 49 publications

Visual depth encoding in populations of neurons with localized receptive fields

Visual depth encoding in populations of neurons with localized receptive fields

Quantitative Analysis of the Responses of V1 Neurons to Horizontal Disparity in Dynamic Random-Dot Stereograms

Early computational processing in binocular vision and depth perception

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