128 resultados para shape recognitions


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The influence of particle shape on the stress-strain response of fine silica sand is investigated experimentally. Two sands from the same source and with the same particle size distribution were examined using Fourier descriptor analysis for particle shape. Their grains were, on average, found to have similar angularity but different elongation. During triaxial stress path testing, the stress-strain behavior of the sands for both loading and creep stages were found to be influenced by particle elongation. In particular, the behavior of the sand with less elongated grains was more like that of rounded glass beads during creep. The results highlight the role of particle shape in stress transmission in granular packings and suggest that shape should be taken more rigorously into consideration in characterizing geomaterials. © 2005 Taylor & Francis Group.

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This paper tackles the novel challenging problem of 3D object phenotype recognition from a single 2D silhouette. To bridge the large pose (articulation or deformation) and camera viewpoint changes between the gallery images and query image, we propose a novel probabilistic inference algorithm based on 3D shape priors. Our approach combines both generative and discriminative learning. We use latent probabilistic generative models to capture 3D shape and pose variations from a set of 3D mesh models. Based on these 3D shape priors, we generate a large number of projections for different phenotype classes, poses, and camera viewpoints, and implement Random Forests to efficiently solve the shape and pose inference problems. By model selection in terms of the silhouette coherency between the query and the projections of 3D shapes synthesized using the galleries, we achieve the phenotype recognition result as well as a fast approximate 3D reconstruction of the query. To verify the efficacy of the proposed approach, we present new datasets which contain over 500 images of various human and shark phenotypes and motions. The experimental results clearly show the benefits of using the 3D priors in the proposed method over previous 2D-based methods. © 2011 IEEE.

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The capability to automatically identify shapes, objects and materials from the image content through direct and indirect methodologies has enabled the development of several civil engineering related applications that assist in the design, construction and maintenance of construction projects. This capability is a product of the technological breakthroughs in the area of Image Processing that has allowed for the development of a large number of digital imaging applications in all industries. In this paper, an automated and content based shape recognition model is presented. This model was devised to enhance the recognition capabilities of our existing material based image retrieval model. The shape recognition model is based on clustering techniques, and specifically those related with material and object segmentation. The model detects the borders of each previously detected material depicted in the image, examines its linearity (length/width ratio) and detects its orientation (horizontal/vertical). The results emonstrate the suitability of this model for construction site image retrieval purposes and reveal the capability of existing clustering technologies to accurately identify the shape of a wealth of materials from construction site images.

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Digital photographs of construction site activities are gradually replacing their traditional paper based counterparts. Existing digital imaging technologies in hardware and software make it easy for site engineers to take numerous photographs of “interesting” processes and activities on a daily basis. The resulting photographic data are evidence of the “as-built” project, and can therefore be used in a number of project life cycle tasks. However, the task of retrieving the relevant photographs needed in these tasks is often burdened by the sheer volume of photographs accumulating in project databases over time and the numerous objects present in each photograph. To solve this problem, the writers have recently developed a number of complementary techniques that can automatically classify and retrieve construction site images according to a variety of criteria (materials, time, date, location, etc.). This paper presents a novel complementary technique that can automatically identify linear (i.e., beam, column) and nonlinear (i.e., wall, slab) construction objects within the image content and use that information to enhance the performance of the writers’ existing construction site image retrieval approach.

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Differential growth of thin elastic bodies furnishes a surprisingly simple explanation of the complex and intriguing shapes of many biological systems, such as plant leaves and organs. Similarly, inelastic strains induced by thermal effects or active materials in layered plates are extensively used to control the curvature of thin engineering structures. Such behaviour inspires us to distinguish and to compare two possible modes of differential growth not normally compared to each other, in order to reveal the full range of out-of-plane shapes of an initially flat disk. The first growth mode, frequently employed by engineers, is characterised by direct bending strains through the thickness, and the second mode, mainly apparent in biological systems, is driven by extensional strains of the middle surface. When each mode is considered separately, it is shown that buckling is common to both modes, leading to bistable shapes: growth from bending strains results in a double-curvature limit at buckling, followed by almost developable deformation in which the Gaussian curvature at buckling is conserved; during extensional growth, out-of-plane distortions occur only when the buckling condition is reached, and the Gaussian curvature continues to increase. When both growth modes are present, it is shown that, generally, larger displacements are obtained under in-plane growth when the disk is relatively thick and growth strains are small, and vice versa. It is also shown that shapes can be mono-, bi-, tri- or neutrally stable, depending on the growth strain levels and the material properties: furthermore, it is shown that certain combinations of growth modes result in a free, or natural, response in which the doubly curved shape of disk exactly matches the imposed strains. Such diverse behaviour, in general, may help to realise more effective actuation schemes for engineering structures. © 2012 Elsevier Ltd. All rights reserved.

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The measurement of cantilever parameters is an essential part of performing a calibrated measurement with an atomic force microscope (AFM). The thermal motion method is a widely used technique for calibrating the spring constant of an AFM cantilever, which can be applied to non-rectangular cantilevers. Given the trend towards high frequency scanning, calibration of non-rectangular cantilevers is of increasing importance. This paper presents two results relevant to cantilever calibration via the thermal motion method. We demonstrate the possibility of using the AFM's phase signal to acquire the thermal motion. This avoids the challenges associated with connecting the raw photodiode signal to a separate spectrum analyser. We also describe how numerical calculations may be used to calculate the parameters needed in a thermal motion calibration of a non-rectangular cantilever. Only accurate knowledge of the relative size of the in-plane dimensions of the cantilever is needed in this computation. We use this pair of results in the calibration of a variety of rectangular and non-rectangular cantilevers. We observe an average difference between the Sader and thermal motion values of cantilever stiffness of 10%.

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We propose a new approach for quantifying regions of interest (ROIs) in medical image data. Rotationally invariant shape descriptors (ISDs) were applied to 3D brain regions extracted from MRI scans of 5 Parkinson's patients and 10 control subjects. We concentrated on the thalamus and the caudate nucleus since prior studies have suggested they are affected in Parkinson's disease (PD). In the caudate, both the ISD and volumetric analyses found significant differences between control and PD subjects. The ISD analysis however revealed additional differences between the left and right caudate nuclei in both control and PD subjects. In the thalamus, the volumetric analysis showed significant differences between PD and control subjects, while ISD analysis found significant differences between the left and right thalami in control subjects but not in PD patients, implying disease-induced shape changes. These results suggest that employing ISDs for ROI characterization both complements and extends traditional volumetric analyses. © 2006 IEEE.

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Rotating stall and surge, two instability mechanisms limiting the performance of aeroengines compressors, are studied on the third-order Moore-Greitzer model. The skewness of the compressor characteristic, a single parameter shape signifier, is shown to determine the key qualitative properties of feedback control.

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An optical and irreversible temperature sensor (e.g., a time-temperature integrator) is reported based on a mechanically embossed chiral-nematic polymer network. The polymer consists of a chemical and a physical (hydrogen-bonded) network and has a reflection band in the visible wavelength range. The sensors are produced by mechanical embossing at elevated temperatures. A relative large compressive deformation (up to 10%) is obtained inducing a shift to shorter wavelength of the reflection band (>30 nm). After embossing, a temperature sensor is obtained that exhibits an irreversible optical response. A permanent color shift to longer wavelengths (red) is observed upon heating of the polymer material to temperatures above the glass transition temperature. It is illustrated that the observed permanent color shift is related to shape memory in the polymer material. The films can be printed on a foil, thus showing that these sensors are potentially interesting as time-temperature integrators for applications in food and pharmaceutical products. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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