A minimalistic approach for fast computation of geodesic distances on triangular meshes

The computation of geodesic distances is an important research topic in Geometry Processing and 3D Shape Analysis as it is a basic component of many methods used in these areas. In this work, we present a minimalistic parallel algorithm based on front propagation to compute approximate geodesic distances on meshes. Our method is practical and simple to implement and does not require any heavy pre-processing. The convergence of our algorithm depends on the number of discrete level sets around the source points from which distance information propagates. To appropriately implement our method on GPUs taking into account memory coalescence problems, we take advantage of a graph representation based on a breadth-first search traversal that works harmoniously with our parallel front propagation approach. We report experiments that show how our method scales with the size of the problem. We compare the mean error and processing time obtained by our method with such measures computed using other methods. Our method produces results in competitive times with almost the same accuracy, especially for large meshes. We also demonstrate its use for solving two classical geometry processing problems: the regular sampling problem and the Voronoi tessellation on meshes.Comment: Preprint submitted to Computers & Graphic

Dictionary Learning-based Inpainting on Triangular Meshes

The problem of inpainting consists of filling missing or damaged regions in images and videos in such a way that the filling pattern does not produce artifacts that deviate from the original data. In addition to restoring the missing data, the inpainting technique can also be used to remove undesired objects. In this work, we address the problem of inpainting on surfaces through a new method based on dictionary learning and sparse coding. Our method learns the dictionary through the subdivision of the mesh into patches and rebuilds the mesh via a method of reconstruction inspired by the Non-local Means method on the computed sparse codes. One of the advantages of our method is that it is capable of filling the missing regions and simultaneously removes noise and enhances important features of the mesh. Moreover, the inpainting result is globally coherent as the representation based on the dictionaries captures all the geometric information in the transformed domain. We present two variations of the method: a direct one, in which the model is reconstructed and restored directly from the representation in the transformed domain and a second one, adaptive, in which the missing regions are recreated iteratively through the successive propagation of the sparse code computed in the hole boundaries, which guides the local reconstructions. The second method produces better results for large regions because the sparse codes of the patches are adapted according to the sparse codes of the boundary patches. Finally, we present and analyze experimental results that demonstrate the performance of our method compared to the literature

Colorimetric kit for detection of methanol in ethanol fuel for monitoring the quality of fuels

A colorimetric kit for methanol detection in ethanol-containing fuels and ease of use in the field was developed and tested. The analysis can detect the presence of methanol in fuels when exceeding specification (0.5% v/v) in about 20 min and its simple instrumentation does not require a specialist. The kit method was successfully validated at gas stations located in São Paulo State and the Federal District

Prefácio à Seção Especial dos Tutoriais do SIBGRAPI'08

Sejam bem-vindos à seção especial dos tutoriais do SIBGRAPI 2008!Os participantes do SIBGRAPI de 2008 tiveram a oportunidade de presenciar um conjunto excepcional de tutoriais que cobriram uma vasta gama de assuntos de interesse da comunidade. Tivemos dois tutoriais introdutórios: o primeiro sobre o uso do OpenCV, uma biblioteca já estabelecida para desenvolvimento de aplicações em visão computacional, e o segundo sobre o uso de processamento de imagens para a elaboração de efeitos especiais. Nossos tutoriais avançados foram também bem diversos. O primeiro tratou sobre o uso de CUDA, uma nova linguagem desenvolvida pela NVIDIA para o uso das placas gráficas de última geração em problemas de computação geral, em aplicações de realidade aumentada.Nosso segundo tutorial avançado lidou com o ajuste de superfícies utilizando pseudo-variedades parametrizadas. Desde a conferência, os autores deste tutorial publicaram o material em outras conferências e revistas, e acharam melhor disponibilizar o material do tutorial juntamente com estas publicações no portal do projeto, localizado em http://w3.impa.br/~lvelho/ppm09/.Desejamos então que todos aproveitem o material dos três tutoriais publicados aqui nesta seção

An adaptive graph for volumetric mesh visualization

AbstractThis work presents an adaptive strategy in order to visualize volumetric data generated from numerical simulations of partial differential equations. The mesh is represented by a graph data structure. Moreover, the Autonomous Leaves Graph is extended to the three-dimensional case. This scheme intends to achieve better transversal cost than a treelike (e.g., bintree, quadtree and octree) space arrangement approach. Furthermore, this strategy intends to reduce the computational cost of constructing the discretization and the visualization of data. The total-ordering of the mesh volumes used in the discretization and the visualization processes is by the 3D Modified Hilbert space-filling Curve. To evaluate the performance, the strategy is applied on a Heat Conduction simulation problem using finite difference discretizations and the experimental results are discussed. Comparisons are made between numerical results obtained when using the Hilbert Curve and its modified version. In addition, experiments are shown when visualization is made from inside and outside the volume. The results expose the efficiency of using this strategy

The use of waste oils and fats to produce high value products : formulation of printing inks involving used frying oils

Óleo residual de fritura foi aquecido a 315 ºC na presença de acetato de níquel (II), sendo obtido um polímero viscoso e uma mistura de hidrocarbonetos e compostos orgânicos oxigenados. Obtiveram-se polímeros com viscosidades diversas, dependendo da agitação, fluxo de N2 e do tempo de reação. Os materiais poliméricos foram utilizados como veículo na formulação de tintas de impressão tipo offset, juntamente com carbonato de cálcio e diversos pigmentos. Foram testadas as formulações obtidas para a impressão de gravuras pela técnica de xilogravura, as quais apresentam desempenho semelhante ao de tintas comerciais. ______________________________________________________________________________________________ ABSTRACTUsed frying oil was heated at 315 ºC in the presence of nickel (II) acetate, leading to a viscous polymer and a mixture of hydrocarbons and oxygenated compounds. Polymers were obtained with different viscosities, depending on the stirring, nitrogen flux and reaction time. The polymeric materials were used as binders in printing ink formulations, together with calcium carbonate and adequate pigments. The prepared formulations were tested to produce gravures by xylograph process, with performance similar to commercial printing inks

Real Time Pixel Art Remasterization on GPUs

Abstract-Several methods have been proposed to overcome the pixel art scaling problem through the years. In this article we describe a novel approach to be applied through a massively parallel architecture that can address this issue in real time. To achieve this we design a local and context independent algorithm that enables an efficient parallel implementation on the GPU, delivering full frames output at response time for the user interaction. Our main goal is to apply the method on full frames of old games, which were based on pixel art graphics until the half of the 1990's, and keep the output frame rate good enough for playing

A Novel Algorithm to Verify the Solution of Geometric Puzzle Games

In this paper, we present a novel algorithm to solve the problem of correctly verifying the solution for geometric puzzles. When compared with others, this approach covers a satisfactory amount of cases. The method comprises the use of sixteen possible relations between polygon edges, which are classified to eliminate those that are not necessarily part of the final figure. This method provides for a precise verification of an arranged set of polygons that must form the same image as the desired solution, without the need of extra meta-data. Only the vertexes themselves (also the edge concavity and center position, when circumference arcs are present) are used the algorithm

DIAGNÓSTICO PRECOCE DE DOENÇAS MAMÁRIAS USANDO IMAGENS TÉRMICAS E APRENDIZADO DE MÁQUINA

O câncer é uma doença que se origina de células mutantes, sem causas bem conhecidas ainda, que se reproduzem descontroladamente, aumentando a perfusão sanguínea e, consequentemente, ocasionando um aumento da temperatura da região tumoral. Essa temperatura é irradiada para a pele e pode ser medida por diversos dispositivos como termômetros e a câmeras térmicas. Na termografia médica (por câmeras infra-vermelho), após a aquisição da imagem térmica, é feita a análise e identificação de padrões térmicos. Tendo em vista que o corpo humano é um sistema praticamente simetrico em relação ao plano sagital (i.e. ao plano que divide o corpo em parte direita e esquerda) , a presença de uma grande alteração no padrão térmico entre as mamas esquerda e direita, é um importante indício de presença de patologias. Este trabalho tem por objetivo verificar a viabilidade do uso de técnicas de reconhecimento de padrões na classificação das imagens disponiveis no projeto ProENG  com pacientes saudáveis ou com portadoras de alguma patologia da mama. Para tanto, destas imagens são extraídas características que permitirão a sua classificação através de técnicas de Inteligência Artificial. Utilizou-se características de três grupos distindos: estatísticas simples, baseadas na geometria fractal e características de fundamentação geoestatística. Foram testados três classificadores, SVM, KNN e Naïve Bayes e duas técnicas de redução de características: PCA e Ganho de Informação. Os resultados se mostraram bastante promissores com uma acurácia próxima de 90% e área abaixo da curva ROC próxima de 0,9%