962 resultados para Contour


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We investigated whether infants from 8 ^ 22 weeks of age were sensitive to the illusory contour created by aligned line terminators. Previous reports of illusory-contour detection in infants under 4 months old could be due to infants' preference for the presence of terminators rather than their configuration. We generated preferential-looking stimuli containing sinusoidal lines whose oscillating, abutting terminators give a strong illusory contour in adult perception. Our experiments demonstrated a preference in infants 8 weeks old and above for an oscillating illusory contour compared with a stimulus containing equal terminator density and movement. Control experiments excluded local line density, or attention to alignment in general, as the basis for this result. In the youngest age group (8 ^ 10 weeks) stimulus velocity appears to be critical in determining the visibility of illusory contours, which is consistent with other data on motion processing at this age. We conclude that, by 2 months of age, the infant's visual system contains the nonlinear mechanisms necessary to extract an illusory contour from aligned terminators.

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The primary purpose of this study was to investigate the effect of skate blade shape on skating performance. A secondary purpose was to evaluate if a change in hollow shape can create additional effects on skating performance. Thirty-seven male ice hockey players (age=18 years, SD=3.4) participated. The intervention consisted of four sharpening trials assessed using three on-ice tests. Participant feedback was also assessed using a Likert scale questionnaire. Statistical analysis included within-subject repeated measures MANOVA of trial by skating variables (p≤0.05). Results revealed Contour 1 enhanced performance compared to baseline on six variables at varsity level and five variables at midget level. Contour 1 enhanced performance compared to Contour 2 on six variables at the varsity and midget levels. Contour 1 also scored highest on the feedback questionnaire. Findings of this study indicate that contouring is a necessary practice to achieve optimal skating performance.

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This paper presents methods for moving object detection in airborne video surveillance. The motion segmentation in the above scenario is usually difficult because of small size of the object, motion of camera, and inconsistency in detected object shape etc. Here we present a motion segmentation system for moving camera video, based on background subtraction. An adaptive background building is used to take advantage of creation of background based on most recent frame. Our proposed system suggests CPU efficient alternative for conventional batch processing based background subtraction systems. We further refine the segmented motion by meanshift based mode association.

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This paper describes a method to achieve the most relevant contours of an image. The presented method proposes to integrate the information of the local contours from chromatic components such as H, S and I, taking into account the criteria of coherence of the local contour orientation values obtained from each of these components. The process is based on parametrizing pixel by pixel the local contours (magnitude and orientation values) from the H, S and I images. This process is carried out individually for each chromatic component. If the criterion of dispersion of the obtained orientation values is high, this chromatic component will lose relevance. A final processing integrates the extracted contours of the three chromatic components, generating the so-called integrated contours image

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In image segmentation, clustering algorithms are very popular because they are intuitive and, some of them, easy to implement. For instance, the k-means is one of the most used in the literature, and many authors successfully compare their new proposal with the results achieved by the k-means. However, it is well known that clustering image segmentation has many problems. For instance, the number of regions of the image has to be known a priori, as well as different initial seed placement (initial clusters) could produce different segmentation results. Most of these algorithms could be slightly improved by considering the coordinates of the image as features in the clustering process (to take spatial region information into account). In this paper we propose a significant improvement of clustering algorithms for image segmentation. The method is qualitatively and quantitative evaluated over a set of synthetic and real images, and compared with classical clustering approaches. Results demonstrate the validity of this new approach

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This article describes a novel algorithmic development extending the contour advective semi-Lagrangian model to include nonconservative effects. The Lagrangian contour representation of finescale tracer fields, such as potential vorticity, allows for conservative, nondiffusive treatment of sharp gradients allowing very high numerical Reynolds numbers. It has been widely employed in accurate geostrophic turbulence and tracer advection simulations. In the present, diabatic version of the model the constraint of conservative dynamics is overcome by including a parallel Eulerian field that absorbs the nonconservative ( diabatic) tendencies. The diabatic buildup in this Eulerian field is limited through regular, controlled transfers of this field to the contour representation. This transfer is done with a fast newly developed contouring algorithm. This model has been implemented for several idealized geometries. In this paper a single-layer doubly periodic geometry is used to demonstrate the validity of the model. The present model converges faster than the analogous semi-Lagrangian models at increased resolutions. At the same nominal spatial resolution the new model is 40 times faster than the analogous semi-Lagrangian model. Results of an orographically forced idealized storm track show nontrivial dependency of storm-track statistics on resolution and on the numerical model employed. If this result is more generally applicable, this may have important consequences for future high-resolution climate modeling.

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This paper describes a novel numerical algorithm for simulating the evolution of fine-scale conservative fields in layer-wise two-dimensional flows, the most important examples of which are the earth's atmosphere and oceans. the algorithm combines two radically different algorithms, one Lagrangian and the other Eulerian, to achieve an unexpected gain in computational efficiency. The algorithm is demonstrated for multi-layer quasi-geostrophic flow, and results are presented for a simulation of a tilted stratospheric polar vortex and of nearly-inviscid quasi-geostrophic turbulence. the turbulence results contradict previous arguments and simulation results that have suggested an ultimate two-dimensional, vertically-coherent character of the flow. Ongoing extensions of the algorithm to the generally ageostrophic flows characteristic of planetary fluid dynamics are outlined.

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Although accuracy of digital elevation models (DEMs) can be quantified and measured in different ways, each is influenced by three main factors: terrain character, sampling strategy and interpolation method. These parameters, and their interaction, are discussed. The generation of DEMs from digitised contours is emphasised because this is the major source of DEMs, particularly within member countries of OEEPE. Such DEMs often exhibit unwelcome artifacts, depending on the interpolation method employed. The origin and magnitude of these effects and how they can be reduced to improve the accuracy of the DEMs are also discussed.