9 resultados para shape descriptors

em Universidad de Alicante


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Feature vectors can be anything from simple surface normals to more complex feature descriptors. Feature extraction is important to solve various computer vision problems: e.g. registration, object recognition and scene understanding. Most of these techniques cannot be computed online due to their complexity and the context where they are applied. Therefore, computing these features in real-time for many points in the scene is impossible. In this work, a hardware-based implementation of 3D feature extraction and 3D object recognition is proposed to accelerate these methods and therefore the entire pipeline of RGBD based computer vision systems where such features are typically used. The use of a GPU as a general purpose processor can achieve considerable speed-ups compared with a CPU implementation. In this work, advantageous results are obtained using the GPU to accelerate the computation of a 3D descriptor based on the calculation of 3D semi-local surface patches of partial views. This allows descriptor computation at several points of a scene in real-time. Benefits of the accelerated descriptor have been demonstrated in object recognition tasks. Source code will be made publicly available as contribution to the Open Source Point Cloud Library.

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Background To analyze and compare the relationship between anterior and posterior corneal shape evaluated by a tomographic system combining the Scheimpflug photography and Placido-disc in keratoconus and normal healthy eyes, as well as to evaluate its potential diagnostic value. Methods Comparative case series including a sample of 161 eyes of 161 subjects with ages ranging from 7 to 66 years and divided into two groups: normal group including 100 healthy eyes of 100 subjects, and keratoconus group including 61 keratoconus eyes of 61 patients. All eyes received a comprehensive ophthalmologic examination including an anterior segment analysis with the Sirius system (CSO). Antero-posterior ratios for corneal curvature (k ratio) and shape factor (p ratio) were calculated. Logistic regression analysis was used to evaluate if some antero–posterior ratios combined with other clinical parameters were predictors of the presence of keratoconus. Results No statistically significant differences between groups were found in the antero–posterior k ratios for 3-, 5- and 7-mm diameter corneal areas (p ≥ 0.09). The antero–posterior p ratio for 4.5- and 8-mm diameter corneal areas was significantly higher in the normal group than in the keratoconus group (p < 0.01). The k ratio for 3, 5, and 7 mm was significantly higher in the keratoconus grade IV subgroup than in the normal group (p < 0.01). Furthermore, significant differences were found in the p ratio between the normal group and the keratoconus grade II subgroup (p ≤ 0.01). Finally, the logistic regression analysis identified as significant independent predictors of the presence of keratoconus (p < 0.01) the 8-mm anterior shape factor, the anterior chamber depth, and the minimal corneal thickness. Conclusions The antero-posterior k and p ratios are parameters with poor prediction ability for keratoconus, in spite of the trend to the presence of more prolate posterior corneal surfaces compared to the anterior in keratoconus eyes.

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Purpose: To evaluate the correlation of the mean curvature and shape factors of both corneal surfaces for different corneal diameters measured with the Scheimpflug photography–based system in keratoconus eyes. Methods: A total of 61 keratoconus eyes of 61 subjects, aged 14 to 64 years, were included in this study. All eyes received a comprehensive ophthalmologic examination including anterior segment and corneal analysis with the Sirius system (CSO): anterior and posterior mean corneal radius for 3, 5, and 7 mm (aKM, pKM), anterior and posterior mean shape factor for 4.5 and 8 mm (ap, pp), central and minimal corneal thickness, and anterior chamber depth. Results: Mean aKM/pKM ratio around 1.20 (range, 0.95–1.48) was found for all corneal diameters (P = 0.24). Weak but significant correlations of this ratio with pachymetric parameters were found (r between −0.28 and −0.34, P < 0.04). The correlation coefficient between aKM and pKM was ≥0.92 for all corneal diameters. A strong and significant correlation was also found between ap and pp (r ≥ 0.86, P < 0.01). The multiple regression analysis revealed that central pKM was significantly correlated with aKM, central corneal thickness, anterior chamber depth, and spherical equivalent (R2 ≥ 0.88, P < 0.01) and that 8 mm pp was significantly correlated with 8 mm ap and age (R2 = 0.89, P < 0.01). Conclusions: Central posterior corneal curvature and shape factor in the keratoconus eye can be consistently predicted from the anterior corneal curvature and shape factor, respectively, in combination with other anatomical and ocular parameters.

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This paper describes a study and analysis of surface normal-base descriptors for 3D object recognition. Specifically, we evaluate the behaviour of descriptors in the recognition process using virtual models of objects created from CAD software. Later, we test them in real scenes using synthetic objects created with a 3D printer from the virtual models. In both cases, the same virtual models are used on the matching process to find similarity. The difference between both experiments is in the type of views used in the tests. Our analysis evaluates three subjects: the effectiveness of 3D descriptors depending on the viewpoint of camera, the geometry complexity of the model and the runtime used to do the recognition process and the success rate to recognize a view of object among the models saved in the database.

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The optical power of a thick spherical lens and its Coddington shape factor are essential magnitudes that characterize its image quality. Here, we propose an experimental procedure and apparatus that allow accurate determination of those magnitudes for any spherical lens from geometrical measurements. The performance of the technique and the used instruments are simple since it only requires a microscope and an optical mouse. The propose overcomes the drawbacks of other devices that need of the refractive index or may damage the lens surfaces, like spherometers, and provides similar results to those from commercial lensmeters.

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This article shows the research carried out by the authors focused on how the shape of structural reinforced concrete elements treated with electrochemical chloride extraction can affect the efficiency of this process. Assuming the current use of different anode systems, the present study considers the comparison of results between conventional anodes based on Ti-RuO2 wire mesh and a cement-based anodic system such as a paste of graphite-cement. Reinforced concrete elements of a meter length were molded to serve as laboratory specimens, to closely represent authentic structural supports, with circular and rectangular sections. Results confirm almost equal performances for both types of anode systems when electrochemical chloride extraction is applied to isotropic structural elements. In the case of anisotropic ones, such as rectangular sections with no uniformly distributed rebar, differences in electrical flow density were detected during the treatment. Those differences were more extreme for Ti-RuO2 mesh anode system. This particular shape effect is evidenced by obtaining the efficiencies of electrochemical chloride extraction in different points of specimens.

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During grasping and intelligent robotic manipulation tasks, the camera position relative to the scene changes dramatically because the robot is moving to adapt its path and correctly grasp objects. This is because the camera is mounted at the robot effector. For this reason, in this type of environment, a visual recognition system must be implemented to recognize and “automatically and autonomously” obtain the positions of objects in the scene. Furthermore, in industrial environments, all objects that are manipulated by robots are made of the same material and cannot be differentiated by features such as texture or color. In this work, first, a study and analysis of 3D recognition descriptors has been completed for application in these environments. Second, a visual recognition system designed from specific distributed client-server architecture has been proposed to be applied in the recognition process of industrial objects without these appearance features. Our system has been implemented to overcome problems of recognition when the objects can only be recognized by geometric shape and the simplicity of shapes could create ambiguity. Finally, some real tests are performed and illustrated to verify the satisfactory performance of the proposed system.

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The voltammetric profile of preferentially shaped platinum nanoparticles has been used to analyze the different sites present on the surface. For the first time, this analysis has been made in NaOH solutions and revisited in sulfuric and perchloric acid media. The comparison with the voltammetric profiles of the model surfaces, that is, single-crystal electrodes, allows assigning the different signals appearing in the voltammograms of the nanoparticle to specific sites on the surface. A good correlation between the shape of the nanoparticle determined by TEM and the voltammetric profile is obtained. For the nanoparticles characterized in alkaline media, the adsorbed species on the surface have been characterized, and three major regions can be identified. Below 0.2 V, the major contribution is due to hydrogen adsorption, whereas above 0.6 V, adsorbed OH is the main species on the surface. Between those values, the signals are due to the competitive adsorption/desorption process of OH/H. New criteria for determining the active area in NaOH solutions has been proposed. In this medium, the total charge density measured between 0.06 and 0.90 V stands for 390 μC cm–2. The areas measured are in perfect agreement with those measured in acid media. Once the nanoparticles have been characterized, the behavior of the nanoparticles toward CO oxidation is analyzed and compared with that observed for single-crystal electrodes.

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Multimetallic shape-controlled nanoparticles offer great opportunities to tune the activity, selectivity, and stability of electrocatalytic surface reactions. However, in many cases, our synthetic control over particle size, composition, and shape is limited requiring trial and error. Deeper atomic-scale insight in the particle formation process would enable more rational syntheses. Here we exemplify this using a family of trimetallic PtNiCo nanooctahedra obtained via a low-temperature, surfactant-free solvothermal synthesis. We analyze the competition between Ni and Co precursors under coreduction “one-step” conditions when the Ni reduction rates prevailed. To tune the Co reduction rate and final content, we develop a “two-step” route and track the evolution of the composition and morphology of the particles at the atomic scale. To achieve this, scanning transmission electron microscopy and energy dispersive X-ray elemental mapping techniques are used. We provide evidence of a heterogeneous element distribution caused by element-specific anisotropic growth and create octahedral nanoparticles with tailored atomic composition like Pt1.5M, PtM, and PtM1.5 (M = Ni + Co). These trimetallic electrocatalysts have been tested toward the oxygen reduction reaction (ORR), showing a greatly enhanced mass activity related to commercial Pt/C and less activity loss than binary PtNi and PtCo after 4000 potential cycles.