Edge coding in human vision: a psychophysical and computational investigation

This thesis presents a study of how edges are detected and encoded by the human visual system. The study begins with theoretical work on the development of a model of edge processing, and includes psychophysical experiments on humans, and computer simulations of these experiments, using the model. The first chapter reviews the literature on edge processing in biological and machine vision, and introduces the mathematical foundations of this area of research. The second chapter gives a formal presentation of a model of edge perception that detects edges and characterizes their blur, contrast and orientation, using Gaussian derivative templates. This model has previously been shown to accurately predict human performance in blur matching tasks with several different types of edge profile. The model provides veridical estimates of the blur and contrast of edges that have a Gaussian integral profile. Since blur and contrast are independent parameters of Gaussian edges, the model predicts that varying one parameter should not affect perception of the other. Psychophysical experiments showed that this prediction is incorrect: reducing the contrast makes an edge look sharper; increasing the blur reduces the perceived contrast. Both of these effects can be explained by introducing a smoothed threshold to one of the processing stages of the model. It is shown that, with this modification,the model can predict the perceived contrast and blur of a number of edge profiles that differ markedly from the ideal Gaussian edge profiles on which the templates are based. With only a few exceptions, the results from all the experiments on blur and contrast perception can be explained reasonably well using one set of parameters for each subject. In the few cases where the model fails, possible extensions to the model are discussed

Connecting psychophysical performance to neuronal response properties II: Contrast decoding and detection

The purpose of this article is to provide mathematical insights into the results of some Monte Carlo simulations published by Tolhurst and colleagues (Clatworthy, Chirimuuta, Lauritzen, & Tolhurst, 2003; Chirimuuta & Tolhurst, 2005a). In these simulations, the contrast of a visual stimulus was encoded by a model spiking neuron or a set of such neurons. The mean spike count of each neuron was given by a sigmoidal function of contrast, the Naka-Rushton function. The actual number of spikes generated on each trial was determined by a doubly stochastic Poisson process. The spike counts were decoded using a Bayesian decoder to give an estimate of the stimulus contrast. Tolhurst and colleagues used the estimated contrast values to assess the model's performance in a number of ways, and they uncovered several relationships between properties of the neurons and characteristics of performance. Although this work made a substantial contribution to our understanding of the links between physiology and perceptual performance, the Monte Carlo simulations provided little insight into why the obtained patterns of results arose or how general they are. We overcame these problems by deriving equations that predict the model's performance. We derived an approximation of the model's decoding precision using Fisher information. We also analyzed the model's contrast detection performance and discovered a previously unknown theoretical connection between the Naka-Rushton contrast-response function and the Weibull psychometric function. Our equations give many insights into the theoretical relationships between physiology and perceptual performance reported by Tolhurst and colleagues, explaining how they arise and how they generalize across the neuronal parameter space

Psychophysical Tests of the Hypothesis of a Bottom-Up Saliency Map in Primary Visual Cortex

A unique vertical bar among horizontal bars is salient and pops out perceptually. Physiological data have suggested that mechanisms in the primary visual cortex (V1) contribute to the high saliency of such a unique basic feature, but indicated little regarding whether V1 plays an essential or peripheral role in input-driven or bottom-up saliency. Meanwhile, a biologically based V1 model has suggested that V1 mechanisms can also explain bottom-up saliencies beyond the pop-out of basic features, such as the low saliency of a unique conjunction feature such as a red vertical bar among red horizontal and green vertical bars, under the hypothesis that the bottom-up saliency at any location is signaled by the activity of the most active cell responding to it regardless of the cell's preferred features such as color and orientation. The model can account for phenomena such as the difficulties in conjunction feature search, asymmetries in visual search, and how background irregularities affect ease of search. In this paper, we report nontrivial predictions from the V1 saliency hypothesis, and their psychophysical tests and confirmations. The prediction that most clearly distinguishes the V1 saliency hypothesis from other models is that task-irrelevant features could interfere in visual search or segmentation tasks which rely significantly on bottom-up saliency. For instance, irrelevant colors can interfere in an orientation-based task, and the presence of horizontal and vertical bars can impair performance in a task based on oblique bars. Furthermore, properties of the intracortical interactions and neural selectivities in V1 predict specific emergent phenomena associated with visual grouping. Our findings support the idea that a bottom-up saliency map can be at a lower visual area than traditionally expected, with implications for top-down selection mechanisms

From filters to features:Scale-space analysis of edge and blur coding in human vision

To make vision possible, the visual nervous system must represent the most informative features in the light pattern captured by the eye. Here we use Gaussian scale-space theory to derive a multiscale model for edge analysis and we test it in perceptual experiments. At all scales there are two stages of spatial filtering. An odd-symmetric, Gaussian first derivative filter provides the input to a Gaussian second derivative filter. Crucially, the output at each stage is half-wave rectified before feeding forward to the next. This creates nonlinear channels selectively responsive to one edge polarity while suppressing spurious or "phantom" edges. The two stages have properties analogous to simple and complex cells in the visual cortex. Edges are found as peaks in a scale-space response map that is the output of the second stage. The position and scale of the peak response identify the location and blur of the edge. The model predicts remarkably accurately our results on human perception of edge location and blur for a wide range of luminance profiles, including the surprising finding that blurred edges look sharper when their length is made shorter. The model enhances our understanding of early vision by integrating computational, physiological, and psychophysical approaches. © ARVO

Face perception inherits low-level binocular adaptation.

In previous work (May & Zhaoping, 2016; May, Zhaoping, & Hibbard, 2012), we have provided evidence that the visual system efficiently encodes binocular information using separately adaptable binocular summation and differencing channels. In that work, binocular test stimuli delivered different grating patterns to the two binocular channels; selective adaptation of one of the binocular channels made participants more likely to see the other channel's grating pattern. In the current study, we extend this paradigm to face perception. Our test stimuli delivered different face images to the two binocular channels, and we found that selective adaptation of one binocular channel biased the observer to perceive the other channel's face image. We show that the perceived identity, gender, emotional expression, or direction of 3-D rotation of a facial test image can be influenced by pre-exposure to binocular random-noise patterns that contain no meaningful spatial structure. Our results provide compelling evidence that face-processing mechanisms can inherit adaptation from low-level sites. Our adaptation paradigm targets the low-level mechanisms in such a way that any response bias or inadvertent adaptation of high-level mechanisms selective for face categories would reduce, rather than produce, the measured effects of adaptation

Multiple Incommensurate Magnetic States in the Kagome Antiferromagnet Na2Mn3Cl8

The kagome lattice can host exotic magnetic phases arising from frustrated and competing magnetic interactions. However, relatively few insulating kagome materials exhibit incommensurate magnetic ordering. Here, we present a study of the magnetic structures and interactions of antiferromagnetic Na$_2$Mn$_3$Cl$_8$ with an undistorted Mn$^{2+}$ kagome network. Using neutron-diffraction and bulk magnetic measurements, we show that Na$_2$Mn$_3$Cl$_8$ hosts two different incommensurate magnetic states, which develop at $T_{N1} = 1.6$ K and $T_{N2} = 0.6$ K. Magnetic Rietveld refinements indicate magnetic propagation vectors of the form $\mathbf{q} = (q_{x},q_{y},\frac{3}{2})$, and our neutron-diffraction data can be well described by cycloidal magnetic structures. By optimizing exchange parameters against magnetic diffuse-scattering data, we show that the spin Hamiltonian contains ferromagnetic nearest-neighbor and antiferromagnetic third-neighbor Heisenberg interactions, with a significant contribution from long-ranged dipolar coupling. This experimentally-determined interaction model is compared with density-functional-theory simulations. Using classical Monte Carlo simulations, we show that these competing interactions explain the experimental observation of multiple incommensurate magnetic phases and may stabilize multi-$\mathbf{q}$ states. Our results expand the known range of magnetic behavior on the kagome lattice.Comment: 13 pages, 8 figure

Crowdsourcing good landmarks for in-vehicle navigation systems

Augmenting navigation systems with landmarks has been posited as a method of improving the effectiveness of the technology and enhancing drivers’ engagement with the environment. However, good navigational landmarks are both laborious to collect and difficult to define. This research aimed to devise a game concept, which could be played by passengers in cars, and would collect useful landmark data as a by-product. The paper describes how a virtual graffiti tagging game concept was created and tested during on-road trials with 38 participants. The data collected in the road trials were then validated using a survey, in which 100 respondents assessed the quality of the landmarks collected and their potential for reuse in navigation applications. Players of the game displayed a consensus in choosing where to place their graffiti tags with over 30% of players selecting the same object to tag in 10 of the 12 locations. Furthermore, significant correlation was found between how highly landmarks were rated in the survey and how frequently they were tagged during the game. The research provides evidence that using crowdsourcing games to collect landmarks does not require large numbers of people, or extensive coverage of an area, to produce suitable candidate landmarks for navigation

Comparative Analysis of Tandem Repeats from Hundreds of Species Reveals Unique Insights into Centromere Evolution

Centromeres are essential for chromosome segregation, yet their DNA sequences evolve rapidly. In most animals and plants that have been studied, centromeres contain megabase-scale arrays of tandem repeats. Despite their importance, very little is known about the degree to which centromere tandem repeats share common properties between different species across different phyla. We used bioinformatic methods to identify high-copy tandem repeats from 282 species using publicly available genomic sequence and our own data. The assumption that the most abundant tandem repeat is the centromere DNA was true for most species whose centromeres have been previously characterized, suggesting this is a general property of genomes. Our methods are compatible with all current sequencing technologies. Long Pacific Biosciences sequence reads allowed us to find tandem repeat monomers up to 1,419 bp. High-copy centromere tandem repeats were found in almost all animal and plant genomes, but repeat monomers were highly variable in sequence composition and in length. Furthermore, phylogenetic analysis of sequence homology showed little evidence of sequence conservation beyond ~50 million years of divergence. We find that despite an overall lack of sequence conservation, centromere tandem repeats from diverse species showed similar modes of evolution, including the appearance of higher order repeat structures in which several polymorphic monomers make up a larger repeating unit. While centromere position in most eukaryotes is epigenetically determined, our results indicate that tandem repeats are highly prevalent at centromeres of both animals and plants. This suggests a functional role for such repeats, perhaps in promoting concerted evolution of centromere DNA across chromosomes