84 resultados para image reconstruction


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The aim of this article was to study the effect of virtual-reality exposure to situations that are emotionally significant for patients with eating disorders (ED) on the stability of body-image distortion and body-image dissatisfaction. A total of 85 ED patients and 108 non-ED students were randomly exposed to four experimental virtual environments: a kitchen with low-calorie food, a kitchen with high-calorie food, a restaurant with low-calorie food, and a restaurant with high-calorie food. In the interval between the presentation of each situation, body-image distortion and body-image dissatisfaction were assessed. Several 2 x 2 x 2 repeated measures analyses of variance (high-calorie vs. low-calorie food x presence vs. absence of people x ED group vs. control group) showed that ED participants had significantly higher levels of body-image distortion and body dissatisfaction after eating high-calorie food than after eating low-calorie food, while control participants reported a similar body image in all situations. The results suggest that body-image distortion and body-image dissatisfaction show both trait and state features. On the one hand, ED patients show a general predisposition to overestimate their body size and to feel more dissatisfied with their body image than controls. On the other hand, these body-image disturbances fluctuate when participants are exposed to virtual situations that are emotionally relevant for them.

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The tourism image is an element that conditions the competitiveness of tourism destinations by making them stand out in the minds of tourists. In this context, marketers of tourism destinations endeavour to create an induced image based on their identity and distinctive characteristics.A number of authors have also recognized the complexity of tourism destinations and the need for coordination and cooperation among all tourism agents, in order to supply a satisfactory tourist product and be competitive in the tourism market. Therefore, tourism agents at the destination need to develop and integrate strategic marketing plans.The aim of this paper is to determine how cities of similar cultures use their resources with the purpose of developing a distinctive induced tourism image to attract tourists and the extent of coordination and cooperation among the various tourism agents of a destination in the process of induced image creation.In order to accomplish these aims, a comparative analysis of the induced image of two cultural cities is presented, Girona (Spain) and Perpignan (France). The induced image is assessed through the content analysis of promotional brochures and the extent of cooperation with in-depth interviews of the main tourism agents of these destinations.Despite the similarities of both cities in terms of tourism resources, results show the use of different attributes to configure the induced image of each destination, as well as a different configuration of the network of tourism agents that participate in the process of induced image creation

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Postprint (published version)

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An unsupervised approach to image segmentation which fuses region and boundary information is presented. The proposed approach takes advantage of the combined use of 3 different strategies: the guidance of seed placement, the control of decision criterion, and the boundary refinement. The new algorithm uses the boundary information to initialize a set of active regions which compete for the pixels in order to segment the whole image. The method is implemented on a multiresolution representation which ensures noise robustness as well as computation efficiency. The accuracy of the segmentation results has been proven through an objective comparative evaluation of the method

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In image processing, segmentation algorithms constitute one of the main focuses of research. In this paper, new image segmentation algorithms based on a hard version of the information bottleneck method are presented. The objective of this method is to extract a compact representation of a variable, considered the input, with minimal loss of mutual information with respect to another variable, considered the output. First, we introduce a split-and-merge algorithm based on the definition of an information channel between a set of regions (input) of the image and the intensity histogram bins (output). From this channel, the maximization of the mutual information gain is used to optimize the image partitioning. Then, the merging process of the regions obtained in the previous phase is carried out by minimizing the loss of mutual information. From the inversion of the above channel, we also present a new histogram clustering algorithm based on the minimization of the mutual information loss, where now the input variable represents the histogram bins and the output is given by the set of regions obtained from the above split-and-merge algorithm. Finally, we introduce two new clustering algorithms which show how the information bottleneck method can be applied to the registration channel obtained when two multimodal images are correctly aligned. Different experiments on 2-D and 3-D images show the behavior of the proposed algorithms

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Describes a method to code a decimated model of an isosurface on an octree representation while maintaining volume data if it is needed. The proposed technique is based on grouping the marching cubes (MC) patterns into five configurations according the topology and the number of planes of the surface that are contained in a cell. Moreover, the discrete number of planes on which the surface lays is fixed. Starting from a complete volume octree, with the isosurface codified at terminal nodes according to the new configuration, a bottom-up strategy is taken for merging cells. Such a strategy allows one to implicitly represent co-planar faces in the upper octree levels without introducing any error. At the end of this merging process, when it is required, a reconstruction strategy is applied to generate the surface contained in the octree intersected leaves. Some examples with medical data demonstrate that a reduction of up to 50% in the number of polygons can be achieved

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Robotic platforms have advanced greatly in terms of their remote sensing capabilities, including obtaining optical information using cameras. Alongside these advances, visual mapping has become a very active research area, which facilitates the mapping of areas inaccessible to humans. This requires the efficient processing of data to increase the final mosaic quality and computational efficiency. In this paper, we propose an efficient image mosaicing algorithm for large area visual mapping in underwater environments using multiple underwater robots. Our method identifies overlapping image pairs in the trajectories carried out by the different robots during the topology estimation process, being this a cornerstone for efficiently mapping large areas of the seafloor. We present comparative results based on challenging real underwater datasets, which simulated multi-robot mapping

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We introduce a method for surface reconstruction from point sets that is able to cope with noise and outliers. First, a splat-based representation is computed from the point set. A robust local 3D RANSAC-based procedure is used to filter the point set for outliers, then a local jet surface - a low-degree surface approximation - is fitted to the inliers. Second, we extract the reconstructed surface in the form of a surface triangle mesh through Delaunay refinement. The Delaunay refinement meshing approach requires computing intersections between line segment queries and the surface to be meshed. In the present case, intersection queries are solved from the set of splats through a 1D RANSAC procedure

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Quickremovalofbiosolidsinaquaculturefacilities,andspeciallyinrecirculatingaquaculturesystems(RAS),isoneofthemostimportantstepinwastemanagement.Sedimentationdynamicsofbiosolidsinanaquaculturetankwilldeterminetheiraccumulationatthebottomofthetank.