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

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Transmitting What Matters: Task-oriented video composition and compression 29

Transmitting What Matters: Task-oriented video composition a...

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

作者： Andalo, Fernanda A. Penatti, Otavio A. B. Testoni, Vanessa Samsung Res Inst Campinas SP Brazil

ISBN: (纸本)9781509035687

We present a simple yet effective framework Transmitting What Matters (TWM) - to generate compressed videos containing only relevant objects targeted to specific computer vision tasks, such as faces for the task of face expression recognition, license plates for the task of optical character recognition, among others. TWM takes advantage of the final desired computer vision task to compose video frames only with the necessary data. The video frames are compressed and can be stored or transmitted to powerful servers where extensive and time-consuming tasks can be performed. We experimentally present the trade-offs between distortion and bitrate for a wide range of compression levels, and the impact generated by compression artifacts on the accuracy of the desired vision task. We show that, for one selected computer vision task, it is possible to dramatically reduce the amount of required data to be stored or transmitted, without compromising accuracy.

关键词： frame composition object detection and tracking video compression computer vision applications

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Large Viscoelastic Fluid Simulation on GPU

Large Viscoelastic Fluid Simulation on GPU

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brazilian symposium on Games and Digital Entertainment (SBGAMES)

作者： Caio José dos Santos Brito André Luiz B. Vieira-e-Silva Mozart William S. Almeida Veronica Teichrieb João Marcelo Xavier Natario Teixeira Voxar Labs Cln-UFPE Recife Brazil Universidade Federal de Pernambuco Recife PE BR Departamento de Eletrônica e Sistemas Universidade Federal de Pernambuco Recife Brazil

Viscoelastic materials, such as gels, gelatin, and mucus, are increasingly present in movies and games. One common method to simulate this kind of fluid is the Smoothed Particle Hydrodynamics (SPH) using a velocity correction which limits the fluid deformation providing visually consistent results. However, it is very time-consuming. This paper presents the acceleration of viscoelastic SPH using graphics processing unit using CUDA being able to simulate a large number of particles, up to 1 million. The method was implemented as an extension of the DualSPHysics open source project and the performance was compared to an OpenMP implementation, being able to achieve an average of 7.76 speedup.

关键词： graphics processing units Viscosity Mathematical model Computational modeling Strain Solid modeling Games

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Enhancement of Underwater images in Low-to-High Turbidity Rivers 29

Enhancement of Underwater Images in Low-to-High Turbidity Ri...

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

作者： Rodrigues, Daily Daleno de O. de Barros, Wagner F. de Queiroz-Neto, Jose P. Fontoura, Anderson G. Carvalho, Jose Reginaldo H. Univ Fed Amazonas IComp BR-69067005 Manaus Amazonas Brazil Inst Fed Amazonas IFAM BR-69100003 Manaus Amazonas Brazil IFNMG Montes Claros MG Brazil

ISBN: (纸本)9781509035687

The demand for efficient enhancement methods of underwater images of the rivers in the Amazon region is increasing. However, most of those in the region present moderate turbidity and low luminosity. This work aims to improve these images by non-linear filtering techniques, which promote the minimization of light interaction characteristics with the environment, loss of the contrast and colors. The proposed method is compared with two others techniques that requires a unique image as input. The results of the proposed method is promising, with better visual quality considering a wide range of experiments with simulation data and real outdoor scenes.

关键词： Underwater images image Enhancement Degraded images

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Oriented image Foresting Transform Segmentation: Connectivity Constraints with Adjustable Width 29

Oriented Image Foresting Transform Segmentation: Connectivit...

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

作者： Mansilla, Lucy A. C. Miranda, Paulo A. V. Univ Sao Paulo Dept Comp Sci BR-05508090 Sao Paulo SP Brazil

ISBN: (纸本)9781509035687

In this work, we extend a novel seed-based segmentation algorithm, which provides global optimum solutions according to a graph-cut measure, subject to high-level boundary constraints: The simultaneously handling of boundary polarity and connectivity constraints. The proposed method incorporates the connectivity constraint in the Oriented image Foresting Transform (OIFT), ensuring the generation of connected objects, but such that the connection between its internal seeds is guaranteed to have a user-controllable minimum width. In other frameworks, such as the min-cut/max-flow algorithm, the connectivity constraint is known to lead to NP-hard problems. In contrast, our method conserves the low complexity of the OIFT algorithm. In the experiments, we show improved results for the segmentation of thin and elongated objects, for the same amount of user interaction. Our dataset of natural images with true segmentation is publicly available to the community.

关键词： image segmentation connectivity constraints boundary polarity image foresting transform

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Interactive Medical image Segmentation by Statistical Seed Models 29

Interactive Medical Image Segmentation by Statistical Seed M...

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

作者： Spina, Thiago Vallin Martins, Samuel Botter Falcao, Alexandre Xavier Univ Estadual Campinas Inst Comp Campinas SP Brazil

ISBN: (纸本)9781509035687

Interactive 3D object segmentation is an important and challenging activity in medical imaging, although it is tedious and error-prone to be done. Automatic segmentation methods aim to replace the user altogether, but require user interaction to produce training data sets of segmented masks and to make error corrections. We propose a complete framework for interactive medical image segmentation, which reduces user effort by automatically providing an initial segmentation result. We develop a Statistical Seed Model (SSM) to this end, that improves from seed sets selected by robot users when reconstructing masks of previously segmented images. The SSM outputs a seed set that may be used to automatically delineate a new test image. The seeds provide both an implicit object shape constraint and a flexible way of interactively correcting segmentation. We demonstrate that our framework decreases the amount of user interaction by a factor of three, when segmenting MR-images of the cerebellum.

关键词： Interactive Medical image Segmentation Object Models Robot Users Segmentation Resuming

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Using 3D Texture and Margin Sharpness Features on Classification of Small Pulmonary Nodules 29

Using 3D Texture and Margin Sharpness Features on Classifica...

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

作者： Felix, Ailton Oliveira, Marcelo Machado, Aydano Raniery, Jose Fed Univ Alagoas UFAL IC Maceio Alagoas Brazil Univ Sao Paulo Ribeirao Preto Med Sch FMRP Sao Paulo Brazil

ISBN: (纸本)9781509035687

The lung cancer is the reason of a lot of deaths on population around the world. An early diagnosis brings a most curable and simpler treatment options. Due to complexity diagnosis of small pulmonary nodules, computer-Aided Diagnosis (CAD) tools provides an assistance to radiologist aiming the improvement in the diagnosis. Extracting relevant image features is of great importance for these tools. In this work we extracted 3D Texture Features (TF) and 3D Margin Sharpness Features (MSF) from the Lung image Database Consortium (LIDC) in order to create a classification model to classify small pulmonary nodules with diameters between 3-10mm. We used three machine learning algorithm: k-Nearest Neighbor (k-NN), Multilayer Perceptron (MLP) and Random Forest (RF). These algorithms were trained by different set of features from the TF and MSF. The classification model with MLP algorithm using the selected features from the integration of TF and MSF achieved the best AUC of 0.820.

关键词： lung cancer small nodules early diagnosis computer-aided diagnosis texture features margin sharpness features classification machine learning

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Assessing Facial image Accordance to ISO/ICAO Requirements 29

Assessing Facial Image Accordance to ISO/ICAO Requirements

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

作者： Parente, R. L. Batista, L. V. Andrezza, Igor L. P. Borges, Erick V. C. L. Mota, Rajiv A. T. Fed Univ Paraiba UFPB Informat Ctr CI Joao Pessoa Paraiba Brazil VSoft Tecnol Joao Pessoa PB Brazil

ISBN: (纸本)9781509035687

Face has been adopted as default biometric validation method and the International Standard Organization (ISO) proposed a standard which states constraints for facial image. This paper presents methods for evaluating face image conformance to the following ISO/ICAO requirements: pixelation, hair across eyes, veil over face and mouth opened. Each requirement is individually evaluated. The algorithm for analyzing pixelation achieved an equal error rate (EER) equals to 1.7%, result very close to state-of-the-art (0.0% EER). The "Hair Across Eyes" analysis method achieved an EER equals to 11.9% which surpass the best state-of-art result (12.4%). The algorithm for evaluating "Veil Over Face" requirement achieved EER equals to 1.2% which also surpass the best state-of-art result (2.5%). The "Mouth Opened" requirement achieved an EER equals to 4.20%, a result compatible with state-of-art rates for this requirement (3.3%).

关键词： Face image quality ICAO ISO/IEC 19794-5 Pixelation Hair across eyes Veil Over Face Mouth Opened

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Diagnosing Leukemia in Blood Smear images Using an Ensemble of Classifiers and Pre-Trained Convolutional Neural Networks

Diagnosing Leukemia in Blood Smear Images Using an Ensemble ...

引用

brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Luis H.S. Vogado Rodrigo De M.S. Veras Alan R. Andrade Flavio H.D. de Araujo Romuere R.V. Silva Kelson R.T. Aires Federal University of Piauí-Teresina Brazil Federal University of Piaui Teresina Brazil

Leukemia is a worldwide disease. In this paper we demonstrate that it is possible to build an automated, efficient and rapid leukemia diagnosis system. We demonstrate that it is possible to improve the precision of current techniques from the literature using the description power of well-known Convolutional Neural Networks (CNNs). We extract features from a blood smear image using pre-trained CNNs in order to obtain an unique image description. Many feature selection techniques were evaluated and we chose PCA to select the features that are in the final descriptor. To classify the images on healthy and pathological we created an ensemble of classifiers with three individual classification algorithms (Support Vector Machine, Multilayer Perceptron and Random Forest). In the tests we obtained an accuracy rate of 100%. Besides the high accuracy rate, the tests showed that our approach requires less processing time than the methods analyzed in this paper, considering the fact that our approach does not use segmentation to obtain specific cell regions from the blood smear image.

关键词： Feature extraction Blood image color analysis Diseases image segmentation Neural networks Support vector machines

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A new descriptor for retrieving 3D objects applied in Congestive Heart Failure diagnosis 29

A new descriptor for retrieving 3D objects applied in Conges...

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

作者： Biscaro, Helton H. Oliveira, Hellyan Bergamasco, Leila C. C. Nunes, Fatima L. S. Univ Sao Paulo Lab Comp Applicat HealthCare Sch Arts Sci & Humanities Polytech Sch Sao Paulo Brazil

ISBN: (纸本)9781509035687

Content-Based image Retrieval (CBIR) aims to retrieve similar graphical objects from large databases based on their contents. CBIR requires definition of descriptors, algorithms that condense information from the object in order to represent it usually as a real number or a vector in Rn. This article presents the Spectral Descriptor, a new descriptor designed for retrieving three-dimensional geometric objects applied to aid the diagnosis of Congestive Heart Failure (CHF). Our descriptor is based on techniques of compressive sensing and rewrites the coordinates of 3D objects vertices on a basis on which they have a sparse representation. Tests with surfaces reconstructed from heart MRI images, specifically from left ventricle, show that the descriptor has presented a good performance, reaching an average precision of approximately 85% for CHF and 71% for non-CHF cases, maintaining high levels of precision. Results also showed that the Spectral Descriptor can decrease the high dimensionality of features vectors in CBIR systems.

关键词： Content-Based image Retrieval (CBIR) Spectral Descriptor Three-dimensional Objects Congestive Heart Failure

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A Graph-Based Approach for Contextual image Segmentation 29

A Graph-Based Approach for Contextual Image Segmentation

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

作者： Souza, Gustavo B. Alves, Gabriel M. Levada, Alexandre L. M. Cruvinel, Paulo E. Marana, Aparecido N. Univ Fed Sao Carlos Sao Carlos SP Brazil Embrapa Instrumentacao Sao Carlos SP Brazil Univ Estadual Paulista Sao Paulo Brazil

ISBN: (纸本)9781509035687

image segmentation is one of the most important tasks in image Analysis since it allows locating the relevant regions of the images and discarding irrelevant information. Any mistake during this phase may cause serious problems to the subsequent methods of the image-based systems. The segmentation process is usually very complex since most of the images present some kind of noise. In this work, two techniques are combined to deal with such problem: one derived from the graph theory and other from the anisotropic filtering methods, both emphasizing the use of contextual information in order to classify each pixel in the image with higher precision. Given a noisy grayscale image, an anisotropic diffusion filter is applied in order to smooth the interior regions of the image, eliminating noise without loosing much information of boundary areas. After that, a graph is built based on the pixels of the obtained diffused image, linking adjacent nodes (pixels) and considering the capacity of the edges as a function of the filter properties. Then, after applying the Ford-Fulkerson algorithm, the minimum cut of the graph is found (following the min cut-max flow theorem), segmenting the object of interest. The results show that the proposed approach outperforms the traditional and well-referenced Otsu's method.

关键词： Min Cut-Max Flow Graph Theory Anisotropic Diffusion image Segmentation

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