953 resultados para Visual motion energy


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Visual motion cues play an important role in animal and humans locomotion without the need to extract actual ego-motion information. This paper demonstrates a method for estimating the visual motion parameters, namely the Time-To-Contact (TTC), Focus of Expansion (FOE), and image angular velocities, from a sparse optical flow estimation registered from a downward looking camera. The presented method is capable of estimating the visual motion parameters in a complicated 6 degrees of freedom motion and in real time with suitable accuracy for mobile robots visual navigation.

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These data result from an investigation examining the interplay between dyadic rapport and consequential behavior-mirroring. Participants responded to a variety of interpersonally-focused pretest measures prior to their engagement in videotaped interdependent tasks (coded for interactional synchrony using Motion Energy Analysis [17,18]). A post-task evaluation of rapport and other related constructs followed each exchange. Four studies shared these same dependent measures, but asked distinct questions: Study 1 (Ndyad = 38) explored the influence of perceived responsibility and gender-specificity of the task; Study 2 (Ndyad = 51) focused on dyad sex-makeup; Studies 3 (Ndyad = 41) and 4 (Ndyad = 63) examined cognitive load impacts on the interactions. Versions of the data are structured with both individual and dyad as the unit of analysis. Our data possess strong reuse potential for theorists interested in dyadic processes and are especially pertinent to questions about dyad agreement and interpersonal perception / behavior association relationships.

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An autonomous energy source within a human body is of key importance in the development of medical implants. This work deals with the modelling and the validation of an energy harvesting device which converts the myocardial contractions into electrical energy. The mechanism consists of a clockwork from a commercially available wrist watch. We developed a physical model which is able to predict the total amount of energy generated when applying an external excitation. For the validation of the model, a custom-made hexapod robot was used to accelerate the harvesting device along a given trajectory. We applied forward kinematics to determine the actual motion experienced by the harvesting device. The motion provides translational as well as rotational motion information for accurate simulations in three-dimensional space. The physical model could be successfully validated.

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The primate visual motion system performs numerous functions essential for survival in a dynamic visual world. Prominent among these functions is the ability to recover and represent the trajectories of objects in a form that facilitates behavioral responses to those movements. The first step toward this goal, which consists of detecting the displacement of retinal image features, has been studied for many years in both psychophysical and neurobiological experiments. Evidence indicates that achievement of this step is computationally straightforward and occurs at the earliest cortical stage. The second step involves the selective integration of retinal motion signals according to the object of origin. Realization of this step is computationally demanding, as the solution is formally underconstrained. It must rely--by definition--upon utilization of retinal cues that are indicative of the spatial relationships within and between objects in the visual scene. Psychophysical experiments have documented this dependence and suggested mechanisms by which it may be achieved. Neurophysiological experiments have provided evidence for a neural substrate that may underlie this selective motion signal integration. Together they paint a coherent portrait of the means by which retinal image motion gives rise to our perceptual experience of moving objects.

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Stirred mills are becoming increasingly used for fine and ultra-fine grinding. This technology is still poorly understood when used in the mineral processing context. This makes process optimisation of such devices problematic. 3D DEM simulations of the flow of grinding media in pilot scale tower mills and pin mills are carried out in order to investigate the relative performance of these stirred mills. Media flow patterns and energy absorption rates and distributions are analysed here. In the second part of this paper, coherent flow structures, equipment wear and mixing and transport efficiency are analysed. (C) 2006 Published by Elsevier Ltd.

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Models of visual motion processing that introduce priors for low speed through Bayesian computations are sometimes treated with scepticism by empirical researchers because of the convenient way in which parameters of the Bayesian priors have been chosen. Using the effects of motion adaptation on motion perception to illustrate, we show that the Bayesian prior, far from being convenient, may be estimated on-line and therefore represents a useful tool by which visual motion processes may be optimized in order to extract the motion signals commonly encountered in every day experience. The prescription for optimization, when combined with system constraints on the transmission of visual information, may lead to an exaggeration of perceptual bias through the process of adaptation. Our approach extends the Bayesian model of visual motion proposed byWeiss et al. [Weiss Y., Simoncelli, E., & Adelson, E. (2002). Motion illusions as optimal perception Nature Neuroscience, 5:598-604.], in suggesting that perceptual bias reflects a compromise taken by a rational system in the face of uncertain signals and system constraints. © 2007.

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Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

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Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

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La prise de décision est un mécanisme qui fait intervenir les structures neuronales supérieures afin d’effectuer un lien entre la perception du signal et l’action. Plusieurs travaux qui cherchent à comprendre les mécanismes de la prise de décision sont menés à divers ni- veaux allant de l’analyse comportementale cognitive jusqu'à la modélisation computationnelle. Le but de ce projet a été d’évaluer d’un instant à l’autre comment la variabilité du signal observé («bruit»), influence la capacité des sujets humains à détecter la direction du mouvement dans un stimulus visuel. Dans ces travaux, nous avons éliminé l’une des sources potentielles de variabilité, la variabilité d’une image à l’autre, dans le nombre de points qui portaient les trois signaux de mouvements cohérents (gauche, droite, et aléatoire) dans les stimuli de Kinématogramme de points aléatoires (KPA), c’est-à-dire la variabilité d’origine périphérique. Les stimuli KPA de type « V6 » étaient des stimuli KPA standard avec une variabilité instantanée du signal, et par contre les stimuli KPA de type « V8 », étaient modifiés pour éliminer la variabilité stochastique due à la variabilité du nombre de pixels d’un instant à l’autre qui portent le signal cohérent. Si la performance des sujets, qui correspond à leur temps de réaction et au nombre de bonnes réponses, diffère en réponse aux stimuli dont le nombre de points en mouvement cohérent varie (V6) ou ne varie pas (V8), ceci serait une preuve que la variabilité d’origine périphérique modulerait le processus décisionnel. Par contre, si la performance des sujets ne diffère pas entre ces deux types de stimuli, ceci serait une preuve que la source majeure de variabilité de performance est d’origine centrale. Dans nos résultats nous avons constaté que le temps de réaction et le nombre de bonnes réponses sont modulés par la preuve nette du mouvement cohérent. De plus on a pu établir qu’en éliminant la variabilité d’origine périphérique définit ci-dessus, on n’observe pas réellement de modification dans les enregistrements. Ce qui nous à amené à penser qu’il n y a pas de distinction claire entre la distribution des erreurs et les bonnes réponses effectuées pour chacun des essais entre les deux stimuli que nous avons utilisé : V6 et V8. C’est donc après avoir mesuré la « quantité d’énergie » que nous avons proposé que la variabilité observée dans les résultats serait probablement d’origine centrale.

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How does the brain make decisions? Speed and accuracy of perceptual decisions covary with certainty in the input, and correlate with the rate of evidence accumulation in parietal and frontal cortical "decision neurons." A biophysically realistic model of interactions within and between Retina/LGN and cortical areas V1, MT, MST, and LIP, gated by basal ganglia, simulates dynamic properties of decision-making in response to ambiguous visual motion stimuli used by Newsome, Shadlen, and colleagues in their neurophysiological experiments. The model clarifies how brain circuits that solve the aperture problem interact with a recurrent competitive network with self-normalizing choice properties to carry out probablistic decisions in real time. Some scientists claim that perception and decision-making can be described using Bayesian inference or related general statistical ideas, that estimate the optimal interpretation of the stimulus given priors and likelihoods. However, such concepts do not propose the neocortical mechanisms that enable perception, and make decisions. The present model explains behavioral and neurophysiological decision-making data without an appeal to Bayesian concepts and, unlike other existing models of these data, generates perceptual representations and choice dynamics in response to the experimental visual stimuli. Quantitative model simulations include the time course of LIP neuronal dynamics, as well as behavioral accuracy and reaction time properties, during both correct and error trials at different levels of input ambiguity in both fixed duration and reaction time tasks. Model MT/MST interactions compute the global direction of random dot motion stimuli, while model LIP computes the stochastic perceptual decision that leads to a saccadic eye movement.

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The aim of this functional magnetic resonance imaging (fMRI) study was to identify human brain areas that are sensitive to the direction of auditory motion. Such directional sensitivity was assessed in a hypothesis-free manner by analyzing fMRI response patterns across the entire brain volume using a spherical-searchlight approach. In addition, we assessed directional sensitivity in three predefined brain areas that have been associated with auditory motion perception in previous neuroimaging studies. These were the primary auditory cortex, the planum temporale and the visual motion complex (hMT/V5+). Our whole-brain analysis revealed that the direction of sound-source movement could be decoded from fMRI response patterns in the right auditory cortex and in a high-level visual area located in the right lateral occipital cortex. Our region-of-interest-based analysis showed that the decoding of the direction of auditory motion was most reliable with activation patterns of the left and right planum temporale. Auditory motion direction could not be decoded from activation patterns in hMT/V5+. These findings provide further evidence for the planum temporale playing a central role in supporting auditory motion perception. In addition, our findings suggest a cross-modal transfer of directional information to high-level visual cortex in healthy humans.

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This paper demonstrates the application of a robust form of pose estimation and scene reconstruction using data from camera images. We demonstrate results that suggest the ability of the algorithm to rival methods of RANSAC based pose estimation polished by bundle adjustment in terms of solution robustness, speed and accuracy, even when given poor initialisations. Our simulated results show the behaviour of the algorithm in a number of novel simulated scenarios reflective of real world cases that show the ability of the algorithm to handle large observation noise and difficult reconstruction scenes. These results have a number of implications for the vision and robotics community, and show that the application of visual motion estimation on robotic platforms in an online fashion is approaching real-world feasibility.

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Activity-dependent modulation of sensory systems has been documented in many organisms, and is likely to be essential for appropriate processing of information during different behavioral states. However, the mechanisms underlying these phenomena, and often their functional consequences, remain poorly characterized. I investigated the role of octopamine neurons in the flight-dependent modulation observed in visual interneurons in the fruit fly Drosophila melanogaster. The vertical system (VS) cells exhibit a boost in their response to visual motion during flight compared to quiescence. Pharmacological application of octopamine evokes responses in quiescent flies that mimic those observed during flight, and octopamine neurons that project to the optic lobes increase in activity during flight. Using genetic tools to manipulate the activity of octopamine neurons, I find that they are both necessary and sufficient for the flight-induced visual boost. This work provides the first evidence that endogenous release of octopamine is involved in state-dependent modulation of visual interneurons in flies. Further, I investigated the role of a single pair of octopamine neurons that project to the optic lobes, and found no evidence that chemical synaptic transmission via these neurons is necessary for the flight boost. However, I found some evidence that activation of these neurons may contribute to the flight boost. Wind stimuli alone are sufficient to generate transient increases in the VS cell response to motion vision, but result in no increase in baseline membrane potential. These results suggest that the flight boost originates not from a central command signal during flight, but from mechanosensory stimuli relayed via the octopamine system. Lastly, in an attempt to understand the functional consequences of the flight boost observed in visual interneurons, we measured the effect of inactivating octopamine neurons in freely flying flies. We found that flies whose octopamine neurons we silenced accelerate less than wild-type flies, consistent with the hypothesis that the flight boost we observe in VS cells is indicative of a gain control mechanism mediated by octopamine neurons. Together, this work serves as the basis for a mechanistic and functional understanding of octopaminergic modulation of vision in flying flies.