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检索条件"任意字段=14th Brazilian Symposium on Computer Graphics and Image Processing"

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Exploded View Diagrams of 3D Grids 28

Exploded View Diagrams of 3D Grids

引用

28th SIBGRAPI Conference on graphics, Patterns and images SIBGRAPI

作者： Martins Filho, Zamir Brazil, Emilio Vital Sousa, Mario Costa Univ Calgary Calgary AB Canada

ISBN: (纸本)9781467379625

We present a system for creating interactive exploded view diagrams in generalized 3D grids. the primary difference between our approach and existing ones is that our technique neither requires geometrical information of the whole model nor any information regarding the relationship among model parts;instead our implementation depends on which grid cells are considered as object of interest, and which view angle to use. To achieve this, we introduce the Explosion Tree, a data structure closely related to a BSP tree, which supports the explosion view diagrams technique based on the relationship between disjoint convex polygons. In this paper we discuss the application of this technique to Corner-Point Grid which has been extensively used for geological modeling and flow simulation. All the data presented in this work consists of real data currently used in the industry.

关键词： Computational Geometry computer graphics

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Content-based diagnostic hysteroscopy summaries for video browsing

Content-based diagnostic hysteroscopy summaries for video br...

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18th brazilian symposium on computer graphics and image processing (SIBGRAPI 2005)

作者： Gaviao, W Scharcanski, J Univ Fed Rio de Janeiro Inst Informat BR-91501970 Porto Alegre RS Brazil

ISBN: (纸本)0769523897

In hospital practice, several diagnostic hysteroscopy videos are produced daily. these videos are continuous (non-interrupted) video sequences, usually recorded in full. However, only a few segments of the recorded videos are relevant from the diagnosis/prognosis point of view, and need to be evaluated and referenced later this paper proposes a new technique to identify clinically relevant segments in diagnostic hysteroscopy videos, producing a rich and compact video summary which supports fast video browsing. Also, our approach facilitates the selection of representative key-frames for reporting the video contents in the patient records. the proposed approach requires two stages. Initially, statistical techniques are used for selecting relevant video segments. then, a post-processing stage merges adjacent video segments that are similar reducing temporal video over-segmentation. Our preliminary experimental results indicate that our method produces compact video summaries containing a selection of clinically relevant video segments. these experimental results were validated by specialists.

关键词： computer aided diagnosis

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A Review of Texture Classification Methods and Databases 30

A Review of Texture Classification Methods and Databases

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30th SIBGRAPI Conference on graphics, Patterns and images Tutorials (SIBGRAPI-T)

作者： Cavalin, Paulo Oliveira, Luiz S. IBM Corp IBM Res Rio De Janeiro RJ Brazil Univ Fed Parana UFPR Dept Informat Curitiba Parana Brazil

ISBN: (纸本)9781538606193

In this survey, we present a review of methods and resources for texture recognition, presenting the most common techniques that have been used in the recent decades, along with current tendencies. that said, this paper covers since the most traditional approaches, for instance texture descriptors such as gray-level co-occurence matrices (GLCM) and Local Binary Patterns (LBP), to more recent approaches such as Convolutional Neural Networks (CNN) and multi-scale patch-based recognition based on encoding approaches such as Fisher Vectors. In addition, we point out relevant references for benchmark datasets, which can help the reader develop and evaluate new methods.

关键词： Texture recognition image recognition Deep Learning

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Fundamentals and Challenges of Generative Adversarial Networks for image-based Applications 35

Fundamentals and Challenges of Generative Adversarial Networ...

引用

35th SIBGRAPI Conference on graphics, Patterns and images (SIBGRAPI)

作者： Trevisan de Souza, Vinicius Luis Dorta Marques, Bruno Augusto Gois, Joao Paulo Univ Fed ABC Santo Andre Brazil

ISBN: (数字)9781665453851

ISBN: (纸本)9781665453851

Significant advances in image-based applications have been achieved in recent years, many of which are arguably due to recent developments in Generative Adversarial Networks (GANs). Although the continuous improvement in the architectures of GAN has significantly increased the quality of synthetic images, this is not without challenges such as training stability and convergence issues, to name a few. In this work, we present the fundamentals and notable architectures of GANs, especially for image-based applications. We also discuss relevant issues such as training problems, diversity generation, and quality assessment (metrics).

关键词： Generative Adversarial Network image manipulation deep image synthesis deep neural network

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BMAX: a bag of features based method for image classification 28

BMAX: a bag of features based method for image classificatio...

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28th SIBGRAPI Conference on graphics, Patterns and images SIBGRAPI

作者： Senna, Pedro Drummond, Isabela Neves Bastos, Guilherme Sousa Univ Fed Itajuba Inst Engn Sistemas & Tecnol Informacao Itajuba MG Brazil Univ Fed Itajuba Inst Matemat & Computacao Itajuba MG Brazil

ISBN: (纸本)9781467379625

this work presents an image classification method based on bag of features, that needs less local features extracted for create a representative description of the image. the feature vector creation process of our approach is inspired in the cortex-like mechanisms used in "Hierarchical Model and X" proposed by Riesenhuber & Poggio. Bag of Max Features - BMAX works with the distance from each visual word to its nearest feature found in the image, instead of occurrence frequency of each word. the motivation to reduce the amount of features used is to obtain a better relation between recognition rate and computational cost. We perform tests in three public images databases generally used as benchmark, and varying the quantity of features extracted. the proposed method can spend up to 60 times less local features than the standard bag of features, with estimate loss around 5% considering recognition rate, that represents up to 17 times reduction in the running time.

关键词： image classification bag-of-features HMAX low feature usage

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Real-Time brazilian License Plate Detection and Recognition Using Deep Convolutional Neural Networks 30

Real-Time Brazilian License Plate Detection and Recognition ...

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30th SIBGRAPI Conference on graphics, Patterns and images Tutorials (SIBGRAPI-T)

作者： Montazzolli, Sergio Jung, Claudio Univ Fed Rio Grande do Sul Informat Inst Porto Alegre RS Brazil

ISBN: (纸本)9781538622193

Automatic License Plate Recognition (ALPR) is an important task with many applications in Intelligent Transportation and Surveillance systems. As in other computer vision tasks, Deep Learning (DL) methods have been recently applied in the context of ALPR, focusing on country-specific plates, such as American or European, Chinese, Indian and Korean. However, either they are not a complete DL-ALPR pipeline, or they are commercial and utilize private datasets and lack detailed information. In this work, we proposed an end-to-end DL-ALPR system for brazilian license plates based on state-of-theart Convolutional Neural Network architectures. Using a publicly available dataset with brazilian plates [1], the system was able to correctly detect and recognize all seven characters of a license plate in 63.18% of the test set, and 97.39% when considering at least five correct characters (partial match). Considering the segmentation and recognition of each character individually, we are able to segment 99% of the characters, and correctly recognize 93% of them.

关键词： Convolution

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Counting Particles: a simple and fast surface reconstruction method for particle-based fluids 35

Counting Particles: a simple and fast surface reconstruction...

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35th SIBGRAPI Conference on graphics, Patterns and images (SIBGRAPI)

作者： Quispe, Filomen Incahuanaco Paiva, Afonso Univ Sao Paulo ICMC Sao Carlos SP Brazil

ISBN: (数字)9781665453851

ISBN: (纸本)9781665453851

We present a novel and efficient surface reconstruction for particle-based fluid methods. Although particle-based methods are practical for computing level-sets that represent liquid interfaces, these methods are computationally expensive when the number of particles increases considerably due to the intense usage of particle approximations. this paper introduces a simple level-set approximation using a discrete indicator function (DIF) defined by counting particles inside grid cells. Our method is fast, easy to code, and can be adapted straightforwardly in particle-based solvers, even implemented in GPU. Moreover, we show the effectiveness of our approach through a set of experiments against prior surface reconstruction methods.

关键词： Surface reconstruction Liquids Smoothing methods image resolution Pipelines graphics processing units computer architecture

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Unsupervised Effectiveness Estimation for image Retrieval using Reciprocal Rank Information 28

Unsupervised Effectiveness Estimation for Image Retrieval us...

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28th SIBGRAPI Conference on graphics, Patterns and images SIBGRAPI

作者： Guimaraes Pedronette, Daniel Carlos Torres, Ricardo da S. State Univ Sao Paulo UNESP Dept Stat Appl Math & Comp Rio Claro Brazil Univ Campinas UNICAMP Inst Comp Recod Lab Campinas SP Brazil

ISBN: (纸本)9781467379625

In this paper, we present an unsupervised approach for estimating the effectiveness of image retrieval results obtained for a given query. the proposed approach does not require any training procedure and the computational efforts needed are very low, since only the top-k results are analyzed. In addition, we also discuss the use of the unsupervised measures in two novel rank aggregation methods, which assign weights to ranked lists according to their effectiveness estimation. An experimental evaluation was conducted considering different datasets and various image descriptors. Experimental results demonstrate the capacity of the proposed measures in correctly estimating the effectiveness of different queries in an unsupervised manner. the linear correlation between the proposed and widely used effectiveness evaluation measures achieves scores up to 0.86 for some descriptors.

关键词： content-based image retrieval unsupervised effectiveness estimation query difficult prediction

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Graph Cuts and Deep Neural Networks for Fire Detection 36

Graph Cuts and Deep Neural Networks for Fire Detection

引用

36th SIBGRAPI Conference on graphics, Patterns and images (SIBGRAPI)

作者： Pereira, Davi Magalhaes Vieira, Marcelo Bernardes Villela, Saulo Moraes Univ Fed Juiz de Fora Dept Comp Sci Juiz De Fora Brazil

ISBN: (纸本)9798350338737;9798350338720

computer vision methods for fire detection have made significant advancements compared to traditional fire detection systems. the incorporation of fire segmentation masks enables precise analysis, offering valuable insights into the origin and spread of fires to prevent future incidents. this paper presents a novel approach that combines deep neural networks, graph cuts, and color thresholding to achieve fine-grained fire segmentation results. By incorporating graph cuts segmentation with global and local color information, our method enhances accuracy and detailed fire detection. As our results show, our method neatly improves recall, with a competitive precision, leading to an effective fire detection framework.

关键词： fire detection fire segmentation image classification graph cut deep learning color thresholding

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Enhancing the Visualization of the Microvasculature of Extrahepatic Bile Ducts Obtained from Confocal Microscopy images 29

Enhancing the Visualization of the Microvasculature of Extra...

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29th SIBGRAPI Conference on graphics, Patterns and images (SIBGRAPI)

作者： Beltran, Lizeth A. C. dos Santos, Jorge Luiz Cruz, Carolina Uribe Freitas, Carla M. D. S. Fed Univ Rio Grande do Sul UFRGS Inst Informat Porto Alegre RS Brazil Univ Beira Interior Ctr Invest Ciencias Saude Covilha Portugal Lab Expt Hepatol & Gastroenterol Porto Alegre RS Brazil

ISBN: (纸本)9781509035687

Confocal microscopy is an important tool for visualizing 3D datasets of fluorescent specimens, and has been used to investigate the structure of biological specimens. However, such images are affected by the noise introduced during the specimen preparation and image acquisition processes. Anisotropic diffusion is a non-linear filter that can significantly improve image quality while removing noise without blurring edges. this study investigates the application of anisotropic diffusion in confocal microscopy images by exploring different models for parameters' estimation. Our data consists of several slices of extrahepatic bile ducts containing a network of small vessels named Peribiliary Vascular Plexus (PVP), which are affected by several sources of noise. Experimental results show that anisotropic diffusion improved the volumetric visualization of the PVP. We validated the results using MSE and PSNR quantitative approaches and qualitative description by an expert user.

关键词： Anisotropic diffusion image processing Confocal microscopic images Volumetric Visualization

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