962 resultados para Motion perception


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Abstract is not available.

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Age-related macular degeneration (AMD) is the leading cause of blindness in the developed world. Increasing dietary intake of lutein- and zeaxanthin-rich foods is a potential means of preventing, or at least slowing the progression of AMD. Zeaxanthin levels in tropical super-sweetcorn was increased from 1.1 to 11.9 µg/g FW through conventional breeding and selection, associated with both an increase in the proportion of zeaxanthin relative to other carotenoids, and a general increase in carotenoid synthesis. Increasing zeaxanthin was associated with a colour shift from traditional ‘canary-yellow’ kernels to a golden-orange colour. Kernel colour was most closely correlated (r2=69%) with an increase in beta-arm carotenoid concentration. Consumer analysis revealed that prior to any knowledge of zeaxanthin-related health benefit, consumers would readily purchase both yellow and gold cobs. Once the health benefit was explained, this extended to deep-gold cobs. Colour difference between regular yellow sweetcorn and high-zeaxanthin sweetcorn could potentially be used as a visual means of differentiating high-zeaxanthin sweetcorn in the marketplace.

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This talk gives an overview of the project "Uncanny Nature", which incoporates a style of animation called Hybrid Stop Motion, that combines physical object armatures with virtual copies. The development of the production pipeline (using a mix of Blender, Dragonframe, Photoscan and Arduino) is discussed, as well as the way that Blender was used throughout the production to visualise, model, animate and composite the elements together.

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The problem of recovering information from measurement data has already been studied for a long time. In the beginning, the methods were mostly empirical, but already towards the end of the sixties Backus and Gilbert started the development of mathematical methods for the interpretation of geophysical data. The problem of recovering information about a physical phenomenon from measurement data is an inverse problem. Throughout this work, the statistical inversion method is used to obtain a solution. Assuming that the measurement vector is a realization of fractional Brownian motion, the goal is to retrieve the amplitude and the Hurst parameter. We prove that under some conditions, the solution of the discretized problem coincides with the solution of the corresponding continuous problem as the number of observations tends to infinity. The measurement data is usually noisy, and we assume the data to be the sum of two vectors: the trend and the noise. Both vectors are supposed to be realizations of fractional Brownian motions, and the goal is to retrieve their parameters using the statistical inversion method. We prove a partial uniqueness of the solution. Moreover, with the support of numerical simulations, we show that in certain cases the solution is reliable and the reconstruction of the trend vector is quite accurate.

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Head motion (HM) is a well known confound in analyses of functional MRI (fMRI) data. Neuroimaging researchers therefore typically treat HM as a nuisance covariate in their analyses. Even so, it is possible that HM shares a common genetic influence with the trait of interest. Here we investigate the extent to which this relationship is due to shared genetic factors, using HM extracted from resting-state fMRI and maternal and self report measures of Inattention and Hyperactivity-Impulsivity from the Strengths and Weaknesses of ADHD Symptoms and Normal Behaviour (SWAN) scales. Our sample consisted of healthy young adult twins (N = 627 (63% females) including 95 MZ and 144 DZ twin pairs, mean age 22, who had mother-reported SWAN; N = 725 (58% females) including 101 MZ and 156 DZ pairs, mean age 25, with self reported SWAN). This design enabled us to distinguish genetic from environmental factors in the association between head movement and ADHD scales. HM was moderately correlated with maternal reports of Inattention (r = 0.17, p-value = 7.4E-5) and Hyperactivity-Impulsivity (r = 0.16, p-value = 2.9E-4), and these associations were mainly due to pleiotropic genetic factors with genetic correlations [95% CIs] of rg = 0.24 [0.02, 0.43] and rg = 0.23 [0.07, 0.39]. Correlations between self-reports and HM were not significant, due largely to increased measurement error. These results indicate that treating HM as a nuisance covariate in neuroimaging studies of ADHD will likely reduce power to detect between-group effects, as the implicit assumption of independence between HM and Inattention or Hyperactivity-Impulsivity is not warranted. The implications of this finding are problematic for fMRI studies of ADHD, as failing to apply HM correction is known to increase the likelihood of false positives. We discuss two ways to circumvent this problem: censoring the motion contaminated frames of the RS-fMRI scan or explicitly modeling the relationship between HM and Inattention or Hyperactivity-Impulsivity

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- Background Following Kapur’s hypothesis [1] that schizophrenia is the intensification of phenomenological experience caused by the upregulation of dopamine, a survey of observed dopamine responses to phenomenal information was conducted. - Method An integrative study. - Results When considered in the light of the ecological theory of perception (ETP) [2] and global workspace theory (GBT) [3] Kapur’s hypothesis makes sense: Both the ETP and the GBT require an agent to attribute salience to perceptual information in order to filter an infinite array of available information and usefully sort information by importance. Dopamine may be the primary agent for this purpose. Thus perception itself is suspected as being a dopamine-mediated, and the symptoms and signs of schizophrenia may therefore be the result of dopamine dysfunction. - Conclusions The application of both ETP and GBT to the dopamine hypothesis gives the hypothesis a much-needed causal mechanism and the confl uence of these theories also provides ETP with a neurological perceptual fi lter. This paper provides a compelling model for schizophrenia; a hypothesis that ties perceptual theory to Kapur ’ s concept of dopamine-mediated salience.

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Peristaltic motion of a micropolar fluid is studied for small amplitudes of peristalic waves under low Reynolds number analysis. The effect of pressure gradient on the secondary motion reveals many interesting and useful results. The critical value of the pressure gradient ensuing the reversal effect in both velocity field and microrotation is evaluated and discussed.

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The motion of a bore over a sloping beach, earlier considered numerically by Keller, Levine & Whitham (1960), is studied by an approximate analytic technique. This technique is an extension of Whitham's (1958) approach for the propagation of shocks into a non-uniform medium. It gives the entire flow behind the bore and is shown to be equivalent to the theory of modulated simple waves of Varley, Ventakaraman & Cumberbatch (1971).

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There are some scenarios in which Unmmaned Aerial Vehicle (UAV) navigation becomes a challenge due to the occlusion of GPS systems signal, the presence of obstacles and constraints in the space in which a UAV operates. An additional challenge is presented when a target whose location is unknown must be found within a confined space. In this paper we present a UAV navigation and target finding mission, modelled as a Partially Observable Markov Decision Process (POMDP) using a state-of-the-art online solver in a real scenario using a low cost commercial multi rotor UAV and a modular system architecture running under the Robotic Operative System (ROS). Using POMDP has several advantages to conventional approaches as they take into account uncertainties in sensor information. We present a framework for testing the mission with simulation tests and real flight tests in which we model the system dynamics and motion and perception uncertainties. The system uses a quad-copter aircraft with an board downwards looking camera without the need of GPS systems while avoiding obstacles within a confined area. Results indicate that the system has 100% success rate in simulation and 80% rate during flight test for finding targets located at different locations.

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Abstract is not available.

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Background The preference amongst parents for heavier infants is in contrast to obesity prevention efforts worldwide. Parents are poor at identifying overweight in older children, but few studies have investigated maternal perception of weight status amongst toddlers and none in the Australian setting. Methods Mothers (n = 290) completed a self-administered questionnaire at child age 12–16 months, defining their child's weight status as underweight, normal weight, somewhat overweight or very overweight. Weight-for-length z-score was derived from measured weight and length, and children categorized as underweight, normal weight, at risk overweight or obese (WHO standards). Objective classification was compared with maternal perception of weight status. Mean weight-for-length z-score was compared across categories of maternal perception using one-way ANOVA. Multinomial logistic regression was used to determine child or maternal characteristics associated with inaccurate weight perception. Results Most children (83%) were perceived as normal weight. Twenty nine were described as underweight, although none were. Sixty-six children were at risk of overweight, but 57 of these perceived as normal weight. Of the 14 children who were overweight, only 4 were identified as somewhat overweight by their mother. Compared with mothers who could accurately classify their normal weight child, mothers who were older had higher odds of perceiving their normal weight child as underweight, while mothers with higher body mass index had slightly higher odds of describing their overweight/at risk child as normal weight. Conclusion The leaner but healthy weight toddler was perceived as underweight, while only the heaviest children were recognized as overweight. Mothers unable to accurately identify children at risk are unlikely to act to prevent further excess weight gain. Practitioners can lead a shift in attitudes towards weight in infants and young children, promoting routine growth monitoring and adequate but not rapid weight gain.

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We present a motion detection algorithm which detects direction of motion at sufficient number of points and thus segregates the edge image into clusters of coherently moving points. Unlike most algorithms for motion analysis, we do not estimate magnitude of velocity vectors or obtain dense motion maps. The motivation is that motion direction information at a number of points seems to be sufficient to evoke perception of motion and hence should be useful in many image processing tasks requiring motion analysis. The algorithm essentially updates the motion at previous time using the current image frame as input in a dynamic fashion. One of the novel features of the algorithm is the use of some feedback mechanism for evidence segregation. This kind of motion analysis can identify regions in the image that are moving together coherently, and such information could be sufficient for many applications that utilize motion such as segmentation, compression, and tracking. We present an algorithm for tracking objects using our motion information to demonstrate the potential of this motion detection algorithm.