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"abstract": "We attack the problem of image-based rendering with occlusions and general camera motions by using distorted multi-perspective images; such images provide multiple-viewpoint photometry similar to the paintings of cubist artists. We take scene geometry, in contrast, to be embodied in mappings of viewing rays from their original 3D intercepts into the warped multi-perspective image space. This approach allows us to render approximations of scenes with occlusions using time-dense and spatially sparse sequences of camera rays, which is a significant improvement over the storage requirements of an equivalent animation sequence. Additional data compression can be achieved using sparse time key-frames as well. Interpolating the paths of sparse time key-rays correctly in image space requires singular interpolation functions with spatial discontinuities. While there are many technical questions yet to be resolved, the employment of these singular interpolation functions in the multi-perspective image space appears to be of potential interest for generating general-viewpoint scene renderings with minimal data storage.",
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"abstract": "In this paper, the Morphological Skeleton Interpolation (MSI) algorithm is presented. It is an efficient shape-based interpolation method used for interpolating slices between successive slices of a 3-D object. It is based on the well known mathematical morphology procedure of morphological skeletonization, that is used as a representation of an object. The proposed morphological skeleton matching process provides translation, rotation and scaling information at the same time. The interpolated slices preserve the shape of the original object slices, when the slices have similar shapes. It can also modify the shape of an object when the successive slices have not similar shapes. Applications on artificial and real data are also presented.",
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"content": "In this paper, the Morphological Skeleton Interpolation (MSI) algorithm is presented. It is an efficient shape-based interpolation method used for interpolating slices between successive slices of a 3-D object. It is based on the well known mathematical morphology procedure of morphological skeletonization, that is used as a representation of an object. The proposed morphological skeleton matching process provides translation, rotation and scaling information at the same time. The interpolated slices preserve the shape of the original object slices, when the slices have similar shapes. It can also modify the shape of an object when the successive slices have not similar shapes. Applications on artificial and real data are also presented.",
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"abstract": "Robust visual tracking is a challenging problem, especially when a target undergoes complete occlusion or leaves and later re-enters the camera view. The mean-shift tracker is an efficient appearance-based tracking algorithm that has become very popular in recent years. Many researchers have developed extensions to the algorithm that improve the appearance model used in target localization. We approach the problem from a slightly different angle and seek to improve the robustness of the mean-shift tracker by integrating an efficient failure recovery mechanism. The proposed method uses a novel application of the STAGE algorithm to efficiently recover a target in the event of tracking failure. The STAGE algorithm boosts the performance of a local search algorithm by iteratively learning an evaluation function to predict good states for initiating searches. STAGE can be viewed as a random-restart algorithm that chooses promising restart states based on the shape of the state space, as estimated using the search trajectories from previous iterations. In the proposed method, an adapted version of STAGE is applied to the mean-shift target localization algorithm (Bhattacharyya coefficient maximization using the mean-shift procedure) to efficiently recover the lost target. Experiments indicate that the proposed method is viable as a technique for recovering from failure caused by complete occlusion or departure from the camera view.",
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"content": "Robust visual tracking is a challenging problem, especially when a target undergoes complete occlusion or leaves and later re-enters the camera view. The mean-shift tracker is an efficient appearance-based tracking algorithm that has become very popular in recent years. Many researchers have developed extensions to the algorithm that improve the appearance model used in target localization. We approach the problem from a slightly different angle and seek to improve the robustness of the mean-shift tracker by integrating an efficient failure recovery mechanism. The proposed method uses a novel application of the STAGE algorithm to efficiently recover a target in the event of tracking failure. The STAGE algorithm boosts the performance of a local search algorithm by iteratively learning an evaluation function to predict good states for initiating searches. STAGE can be viewed as a random-restart algorithm that chooses promising restart states based on the shape of the state space, as estimated using the search trajectories from previous iterations. In the proposed method, an adapted version of STAGE is applied to the mean-shift target localization algorithm (Bhattacharyya coefficient maximization using the mean-shift procedure) to efficiently recover the lost target. Experiments indicate that the proposed method is viable as a technique for recovering from failure caused by complete occlusion or departure from the camera view.",
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"abstract": "The transformation or blending of one 2D shape into another usually operates on sets of discrete points approximating the objects. This relies on a series of evenly distributed or properly positioned points on the boundary of the objects. Characteristics of the objects are not well considered. This paper presents a technique for transforming or blending shapes represented as a series of curve segments. Transformation of the shapes is attained by establishing correspondence between pairs of features of the objects. Based on an estimation of the sharpness of a corner on the boundary of a 2D contour, vertices are generated on sharp corners of the shapes and hence dividing the boundary of the shapes into elements. Correspondence between the elements of the shape is then established before the correspondence between points on the elements is established. This allows special features of the shapes to be retained in the blending operation which is essential in product and industrial design.",
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"doi": "10.1109/CVPR.2004.1315185",
"title": "2D-shape analysis using conformal mapping",
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"abstract": "The study of 2D shapes and their similarities is a central problem in the field of vision. It arises in particular from the task of classifying and recognizing objects from their observed silhouette. Defining natural distances between 2D shapes creates a metric space of shapes, whose mathematical structure is inherently relevant to the classification task. One intriguing metric space comes from using conformal mappings of 2D shapes into each other, via the theory of Teichmuller spaces. In this space, every simple closed curve in the plane (a \"shape\") is represented by a \"fingerprint\", which is a diffeomorphism of the unit circle to itself (a differentiable and invertible, periodic function). More precisely, every shape defines to a unique equivalence class of such diffeomorphisms up to right multiplication by a Mobius map. The fingerprint does not change if the shape is varied by translations and scaling and any such equivalence class comes from some shape. This coset space, equipped with the infinitesimal Weil-Petersson (WP) Riemannian norm is a metric space. In this space, it appears very likely to be true that the shortest path between each two shapes is unique, and is given by a geodesic connecting them. Their distance from each other is given by integrating the WP-norm along that geodesic. In this paper we concentrate on solving the \"welding\" problem of \"sewing\" together conformally the interior and exterior of the unit circle, glued on the unit circle by a given diffeomorphism, to obtain the unique 2D shape associated with this diffeomorphism. These allow us to go back and forth between 2D shapes and their representing diffeomorphisms in this \"space of shapes\".",
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"abstract": "This study aims to determine the correct amount of components to formulate a mixture of Short-Reinforced Fiber Cement Composite (SRFCC) material, characterize its rheological behavior, and evaluate its performance in the additive manufacturing process. Basic concepts from rheology and cement-based materials were used, making emphasis in their applications for manufacturing processes. The experimentation procedures for a SRFCC were described. In addition, the experimental extrusion system is depicted, in which the validity of the material was verified according to its behavior during the 3D printing process. The results derived from the rheological characterization were presented, allowing for the determination of behavioral and intrinsic properties of the material. Lastly, a series of optimal parameters for a successful extrusion process was established.",
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"affiliation": "Dept. de Cienc. de la Energia y Mec., Univ. de las Fuerzas Armadas ESPE, Sangolquí, Ecuador",
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"abstract": "In this paper an outline is presented of historical and current developments in the application of recurrent Taylor series to the integration of systems of ordinary differential equations. The idea of an extremely accurate and fast method for numerical solutions of differential equations is presented in the paper. In general Taylor series are not included or not even mentioned in surveys on numerical integration techniques as the programs were written by mathematicians with the main objective of demonstrating the feasibility of the concept and with the goal of providing integration algorithms of very high accuracy. For this reason the programs should be looked upon as a stimulus for writing more advanced software employing Taylor series better able to compete with programs using other methods. An attempt in this direction is TKSL, a program the results of which will be dealt with.",
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"abstract": "Based on electromagnetic scattering theory, Mie scattering theory and Monte Carlo method are used to analyze the radiation characteristics of SiC particles with different distribution forms. The radiation characteristics of different particle size distributions were obtained by simulation. The results shows that the form of particle size distribution has a significant impact on the spectral transmittance of particle swarms. The proportion of particles of different sizes in the distribution, the dispersion, and the span of particle size scale all affect the infrared extinction performance of particle swarms in varying degrees. Among them, the proportion of particles of specific size is the most influential factor, which is a necessary factor to ensure the existence and amplitude of particle characteristic spectra. The relationship between particle size distribution and radiation characteristics was also analyzed by static and dynamic infrared spectroscopy, which showed that increasing the proportion of particles in the 0.16~2.5 μm particle size range of SiC particle swarm can comprehensively improve their extinction performance.",
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{
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"content": "Based on electromagnetic scattering theory, Mie scattering theory and Monte Carlo method are used to analyze the radiation characteristics of SiC particles with different distribution forms. The radiation characteristics of different particle size distributions were obtained by simulation. The results shows that the form of particle size distribution has a significant impact on the spectral transmittance of particle swarms. The proportion of particles of different sizes in the distribution, the dispersion, and the span of particle size scale all affect the infrared extinction performance of particle swarms in varying degrees. Among them, the proportion of particles of specific size is the most influential factor, which is a necessary factor to ensure the existence and amplitude of particle characteristic spectra. The relationship between particle size distribution and radiation characteristics was also analyzed by static and dynamic infrared spectroscopy, which showed that increasing the proportion of particles in the 0.16~2.5 μm particle size range of SiC particle swarm can comprehensively improve their extinction performance.",
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"normalizedAbstract": "Based on electromagnetic scattering theory, Mie scattering theory and Monte Carlo method are used to analyze the radiation characteristics of SiC particles with different distribution forms. The radiation characteristics of different particle size distributions were obtained by simulation. The results shows that the form of particle size distribution has a significant impact on the spectral transmittance of particle swarms. The proportion of particles of different sizes in the distribution, the dispersion, and the span of particle size scale all affect the infrared extinction performance of particle swarms in varying degrees. Among them, the proportion of particles of specific size is the most influential factor, which is a necessary factor to ensure the existence and amplitude of particle characteristic spectra. The relationship between particle size distribution and radiation characteristics was also analyzed by static and dynamic infrared spectroscopy, which showed that increasing the proportion of particles in the 0.16~2.5 μm particle size range of SiC particle swarm can comprehensively improve their extinction performance.",
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"affiliation": "Beijing University of Technology, National Key Laboratory of Science and Technology on Test Physics & Numerical Mathematics,Beijing,China",
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"abstract": "The basic physical characteristics of fog are analysed in this paper. According to Mie theory, the average extinction parameters of THz wave and infrared radiation of fog droplets at different frequencies are calculated. Based on the weighted MC method, the relationship between the transmittance of THz wave in advection fog and radiation fog, visibility and transmission distance is calculated and compared with the transmittance of infrared radiation. The results show that under the same conditions, the lower the frequency of THz wave is, the higher the transmittance is, and the transmittance of terahertz wave is much larger than that of infrared radiation. It has stronger ability to penetrate thick fog. When the visibility is the same, advection fog has larger droplets than radiation fog. The transmission of terahertz wave in radiation fog is obviously larger than that in advection fog. Advection fog has greater influence on the transmission of terahertz wave.",
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"content": "The basic physical characteristics of fog are analysed in this paper. According to Mie theory, the average extinction parameters of THz wave and infrared radiation of fog droplets at different frequencies are calculated. Based on the weighted MC method, the relationship between the transmittance of THz wave in advection fog and radiation fog, visibility and transmission distance is calculated and compared with the transmittance of infrared radiation. The results show that under the same conditions, the lower the frequency of THz wave is, the higher the transmittance is, and the transmittance of terahertz wave is much larger than that of infrared radiation. It has stronger ability to penetrate thick fog. When the visibility is the same, advection fog has larger droplets than radiation fog. The transmission of terahertz wave in radiation fog is obviously larger than that in advection fog. Advection fog has greater influence on the transmission of terahertz wave.",
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"abstract": "Functionally Graded Materials (FGMs) have been extensively studied in the past few decades. With increasingly powerful computers and highly precise measuring technologies, initial macro-scale volume fractions based FGM characterization has been extended to micro structural models, enabling more delicate and accurate description of FGMs in computer-aided design and analysis. This paper presents a new design approach to modeling porous structures with graded porosities and pore distributions. A novel digital model based on stochastic Voronoi diagram and B-Spline representation is proposed. Using such a model, generic porous structures with graded and irregularly shaped pores can be easily designed. The proposed approach is therefore useful for downstream model validations, simulations as well as micro structural optimizations.",
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"content": "Functionally Graded Materials (FGMs) have been extensively studied in the past few decades. With increasingly powerful computers and highly precise measuring technologies, initial macro-scale volume fractions based FGM characterization has been extended to micro structural models, enabling more delicate and accurate description of FGMs in computer-aided design and analysis. This paper presents a new design approach to modeling porous structures with graded porosities and pore distributions. A novel digital model based on stochastic Voronoi diagram and B-Spline representation is proposed. Using such a model, generic porous structures with graded and irregularly shaped pores can be easily designed. The proposed approach is therefore useful for downstream model validations, simulations as well as micro structural optimizations.",
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"fno": "4293a099",
"keywords": [
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"abstract": "This paper feacture the results of a simulation of real materials of unidirectional porous nano structures of TiO2 (1D), through the implementation of a simulated heuristic algorithm. it is demonstrated the efficiency of the system it is necessary to find a fractal index close to three, in this way, the system indicates a greater penetration of liquids in the materials, a greater madness, a greater unidirectionality. displaying the input data of the simulation are efficient to apply in real materials. These data were the distance between pores and the radius size for each of the samples. The simulation with a fractal index of 2.94, 2.96, 2.99 and 2.97 in the different samples are higher quality, which confirms that the geometry of nanotube matrices of TiO2 can reach the best unidirectionality, using a numerical simulation. This simulator is important as an alternative to characterize porous materials in cases where there is no technical infrastructure for the complete physical characterization of nanoporous materials.",
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{
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"content": "This paper feacture the results of a simulation of real materials of unidirectional porous nano structures of TiO2 (1D), through the implementation of a simulated heuristic algorithm. it is demonstrated the efficiency of the system it is necessary to find a fractal index close to three, in this way, the system indicates a greater penetration of liquids in the materials, a greater madness, a greater unidirectionality. displaying the input data of the simulation are efficient to apply in real materials. These data were the distance between pores and the radius size for each of the samples. The simulation with a fractal index of 2.94, 2.96, 2.99 and 2.97 in the different samples are higher quality, which confirms that the geometry of nanotube matrices of TiO2 can reach the best unidirectionality, using a numerical simulation. This simulator is important as an alternative to characterize porous materials in cases where there is no technical infrastructure for the complete physical characterization of nanoporous materials.",
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"abstract": "Real noisy-clean pairs on a large scale are costly and difficult to obtain. Meanwhile, supervised denoisers trained on synthetic data perform poorly in practice. Self-supervised denoisers, which learn only from single noisy images, solve the data collection problem. However, self-supervised denoising methods, especially blindspot-driven ones, suffer sizable information loss during input or network design. The absence of valuable information dramatically reduces the upper bound of denoising performance. In this paper, we propose a simple yet efficient approach called Blind2Unblind to overcome the information loss in blindspot-driven denoising methods. First, we introduce a global-aware mask mapper that enables global perception and accelerates training. The mask mapper samples all pixels at blind spots on denoised volumes and maps them to the same channel, allowing the loss function to optimize all blind spots at once. Second, we propose a revisible loss to train the denoising network and make blind spots visible. The denoiser can learn directly from raw noise images without losing information or being trapped in identity mapping. We also theoretically analyze the convergence of the revisible loss. Extensive experiments on synthetic and real-world datasets demonstrate the superior performance of our approach compared to previous work. Code is available at https://github.com/demonsjin/Blind2Unblind.",
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