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Restoration of images Affected by Welding Fume 31

Restoration of Images Affected by Welding Fume

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31st Conference on graphics, Patterns and images (SIBGRAPI)

作者： Vaz-, Edwilson, Jr. Drews-, Paulo, Jr. steffens, Cristiano Fed Univ Rio Grande Ctr Computat Sci C3 Rio Grande Brazil

ISBN: (纸本)9781538692646

Machine vision performs an important role in many applications, including robotics. Combined with classical instrumentation, welding robots can use a camera to perceive the scene and take a decision. A camera attached to the robot body and machine vision system work as the eyes of the robot during the welding process. However, image-based systems are susceptible to the interference of fumes, sparks, dust, and artifacts generated as a side effect of the welding process. Fume can adhere to the lenses and degrades the image, introducing a negative impact on the processing pipeline. This paper proposes a novel image fusion based algorithm that minimizes the effects caused by the fume adhered to the camera lens. Results show the proposed method is able to enhance the overall image quality, outperforming classical alternatives for similar problems.

关键词： Welding Cameras Lenses Robot vision systems Glass image fusion

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A Benchmark Methodology for Child Pornography Detection 31

A Benchmark Methodology for Child Pornography Detection

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31st Conference on graphics, Patterns and images (SIBGRAPI)

作者： Macedo, Joao Costa, Filipe dos Santos, Jefersson A. Univ Fed Minas Gerais Dept Comp Sci Belo Horizonte MG Brazil Brazilian Fed Police Belo Horizonte MG Brazil CPqD Image & Speech Proc Management Campinas SP Brazil

ISBN: (纸本)9781538692646

The acquisition and distribution of child sexual content are some of the most important concerns for legislative systems and law enforcement agencies around the world. There is a great demand for automatic detection of child pornography, mainly due to the large amount of existent data and the facility someone can share this content over the internet. Although there are some proposed methods to automatically detect child pornography content in the literature, there is no available dataset to assess and compare the performance of these methods due to legal restrictions, considering that in many countries the distribution or possession of this material is a crime by Law. To mitigate this problem, we work with the brazilian Federal Police to structure and organize a benchmark methodology for child pornography to make it possible the comparison of distinct categories of child pornography detectors. Therefore, we present in this paper the used methodology for the creation of a new annotated dataset of images of child pornography. We also propose a child pornography detection step-wise methodology based on automatic age estimation combined with a pornography detector, which is evaluated using the described benchmark dataset. The proposed approach achieved results (79.84% accuracy) that overcome two tools currently used by the brazilian Federal Police.

关键词： Face Estimation Law enforcement Detectors image color analysis Visualization Feature extraction

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Multimodal Human Action Recognition Based on a Fusion of Dynamic images using CNN descriptors 31

Multimodal Human Action Recognition Based on a Fusion of Dyn...

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31st Conference on graphics, Patterns and images (SIBGRAPI)

作者： Cardenas, Edwin Escobedo Chavez, Guillermo Camara Fed Univ Ouro Preto UFOP Dept Comp Sci DECOM Ouro Preto MG Brazil

ISBN: (纸本)9781538692646

In this paper, we propose the use of dynamicimages-based approach for action recognition. Specifically, we exploit the multimodal information recorded by a Kinect sensor (RGB-D and skeleton joint data). We combine several ideas from rank pooling and skeleton optical spectra to generate dynamic images to summarize an action sequence into single flow images. We group our dynamic images into five groups: a dynamic color group (DC);a dynamic depth group (DD) and three dynamic skeleton groups (DXY, DYZ, DXZ). As action is composed of different postures along time, we generated N different dynamic images with the main postures for each dynamic group. Next, we applied a pre-trained flow-CNN to extract spatiotemporal features with a max-mean aggregation. The proposed method was evaluated on a public benchmark dataset, the UTD-MHAD, and achieved the state-of-the-art result.

关键词： Skeleton Feature extraction Dynamics Spatiotemporal phenomena image color analysis Video sequences Robot sensing systems

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An Architecture for Collision Risk Prediction for Visually Impaired People 31

An Architecture for Collision Risk Prediction for Visually I...

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31st Conference on graphics, Patterns and images (SIBGRAPI)

作者： Cordeiro, Natal Henrique Pedrino, Emerson Carlos Fed Inst Sao Paulo Dept Comp Votuporanga SP Brazil Univ Fed Sao Carlos Dept Comp Sci Sao Carlos SP Brazil

ISBN: (纸本)9781538692646

The production of sensory substitution equipment for the visually impaired (VIP) is growing. The aim of this project is to understand the VIP context and predict the risks of collision for the VIP, following an analysis of the position, distance, size and motion of the objects present in their environment. This understanding is refined by data fusion steps applied to the Situation Awareness model to predict possible impacts in the near future. With this goal, a new architecture was designed, composed of systems that detect free passages, static objects, dynamic objects and the paths of these dynamic objects. The detected data was mapped into a 3D plane verifying positions and sizes. For the fusion, a method was developed that compared four more general classifiers in order to verify which presented greater reliability in the given context. These classifiers allowed inferences to be made when analyzing the risks of collision in different directions. The architecture designed for risk prediction is the main contribution of this project.

关键词： computer architecture Cameras Indoor environment Data integration Surface acoustic waves Radiofrequency identification

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Hybrid Cloud Rendering System for Massive CAD Models 31

Hybrid Cloud Rendering System for Massive CAD Models

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31st Conference on graphics, Patterns and images (SIBGRAPI)

作者： Moreira, Andre Ivson, Paulo Celes, Waldemar Pontifical Catholic Univ Rio de Janeiro PUC Rio Tecgraf Inst Rio De Janeiro Brazil Pontifical Catholic Univ Rio de Janeiro PUC Rio Dept Comp Sci Rio De Janeiro Brazil

ISBN: (纸本)9781538692646

The recent advances in cloud services enable an increasing number of applications to offload their intensive tasks to remote computers. Cloud rendering comprises a set of services capable of rendering a 3D scene on a remote workstation. Notable progress in this field has been made by cloud gaming services. However, a gap remains between existing cloud rendering systems and other graphics-intensive applications, such as visualization of computer-Aided Design (CAD) models. Existing cloud gaming services are not suitable to efficiently render these particular 3D scenes. CAD models contain many more objects than a regular game scene, requiring specific assumptions and optimizations to deliver an interactive user experience. In this work, we discuss and propose a novel hybrid cloud rendering system for massive 3D CAD models of industrial plants. The obtained results show that our technique can achieve high frame rates with satisfactory image quality even in a constrained environment, such as a high latency network or obsolete computer hardware.

关键词： Rendering (computer graphics) Servers Solid modeling Delays Cloud computing Three-dimensional displays Computational modeling

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Factors influencing the perception of realism in synthetic facial expressions 31

Factors influencing the perception of realism in synthetic f...

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31st Conference on graphics, Patterns and images (SIBGRAPI)

作者： Testa, Rafael Luiz Machado-Lima, Ariane Nunes, Fatima L. S. Univ Sao Paulo Sch Arts Sci & Humanities Sao Paulo Brazil Univ Sao Paulo Escola Politecn Sao Paulo Brazil

ISBN: (纸本)9781538692646

One way to synthesize facial expressions is to change an image to represent the desired emotion and it is useful in entertainment, diagnostic and psychiatric disorders therapy applications. Despite several existing approaches, there is little discussion about factors that contribute or hinder the perception of realism in synthetic facial expressions images. After presenting an approach for facial expressions synthesis through the deformation of facial features, this paper provides an evaluation by 155 volunteers regarding the realism of synthesized images. The proposed facial expression synthesis aims to generate new images using two source images (neutral and expressive face) and changing the expression in a target image (neutral face). The results suggest that assignment of realism depends on the type of image (real or synthetic). However, the synthesis presents images that can be considered realistic, especially for the expression of happiness. Finally, while factors such as color difference between subsequent regions and unnatural-sized facial features contribute to less realism, other factors such as the presence of wrinkles contribute to a greater assignment of realism to images.

关键词： Face Databases Facial features strain image reconstruction Feature extraction Visualization

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GuidedNet: Single image Dehazing Using an End-to-end Convolutional Neural Network 31

GuidedNet: Single Image Dehazing Using an End-to-end Convolu...

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31st Conference on graphics, Patterns and images (SIBGRAPI)

作者： Goncalves, Lucas T. Gaya, Joel O. Drews-, Paulo, Jr. Botelho, Silvia S. C. Univ Fed Rio Grande FURG Ctr Computat Sci C3 Intelligent Robot & Automat Grp NAUTEC Rio Grande Brazil

ISBN: (纸本)9781538692646

Poor visibility is a common problem when capturing images in participating mediums such as mist or water. The problem of generating a haze-free image based on a hazy one can be described as image dehazing. Previous approaches dealt with this problem using physical models based on priors and simplifications. In this paper, we demonstrate that an end-to-end convolutional neural network is able to learn the dehazing process with no parameters or priors required, resulting in a more generic method. Even though our model is trained entirely with hazy indoor images, we are able to fully restore outdoor images with real haze. Also, we propose an architecture containing the novel Guided Layers, introduced in order to reduce the loss of spatial information while restoring the images. Our method outperforms other machine learning based models, yielding superior results both qualitatively and quantitatively.

关键词： Atmospheric modeling Neural networks image restoration Training Scattering Degradation Network architecture

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Extracting Visual Encodings from Map Chart images with Color-encoded Scalar Values 31

Extracting Visual Encodings from Map Chart Images with Color...

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31st Conference on graphics, Patterns and images (SIBGRAPI)

作者： Mayhua, Angela Gomez-Nieto, Erick Heer, Jeffrey Poco, Jorge Univ Catolica San Pablo Arequipa Peru Univ Washington Seattle WA 98195 USA Fundacao Getulio Vargas Rio De Janeiro Brazil

ISBN: (纸本)9781538692646

Map charts are used in diverse domains to show geographic data (e.g., climate research, oceanography, business analysis, etc.). These charts can be found in news articles, scientific papers, and on the Web. However, many map charts are available only as bitmap images, hindering machine interpretation of the visualized data for indexing and reuse. We propose a pipeline to recover both the visual encodings and underlying data from bitmap images of geographic maps with color-encoded scalar values. We evaluate our results using map images from scientific documents, achieving high accuracy along each step of our proposal. In addition, we present two applications: data extraction and map reprojection to enable improved visual representations of map charts.

关键词： image color analysis Data mining Bars Visualization Data visualization Encoding image coding

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Deep Transfer Learning for Segmentation of Anatomical structures in Chest Radiographs 31

Deep Transfer Learning for Segmentation of Anatomical Struct...

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31st Conference on graphics, Patterns and images (SIBGRAPI)

作者： Oliveira, Hugo dos Santos, Jefersson A. Univ Fed Minas Gerais Dept Comp Sci BR-31270901 Belo Horizonte MG Brazil

ISBN: (纸本)9781538692646

Segmentation of anatomical structures in Chest Posterior-Anterior Radiographs is a classical task on biomedical image analysis. Deep Learning has been widely used for detection and diagnosis of illnesses in several medical image modalities over the last years, but the portability of deep methods is still limited, hampering the reusability of pre-trained models in new data. We address this problem by proposing a novel method for Cross-Dataset Transfer Learning in Chest X-Ray images based on Unsupervised image Translation architectures. Our Transfer Learning approach achieved Jaccard values of 88.20% on lung field segmentation in the Montgomery Set by using a pre-trained model on the JSRT dataset and no labeled data from the target dataset. Several experiments in unsupervised and semi-supervised transfer were performed and our method consistently outperformed simple fine-tuning when a limited amount of labels is used. Qualitative analysis on the tasks of clavicle and heart segmentation are also performed on Montgomery samples and pre-trained models from JSRT dataset. Our secondary contributions encompass several experiments in anatomical structure segmentation on JSRT, achieving state-of-the-art results in lung field (96.02%), heart (89.64%) and clavicle segmentation (87.30%).

关键词： image segmentation Task analysis Lung computer architecture Heart Biomedical imaging Semantics

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RISF: Recursive Iterative Spanning Forest for Superpixel Segmentation 31

RISF: Recursive Iterative Spanning Forest for Superpixel Seg...

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31st Conference on graphics, Patterns and images (SIBGRAPI)

作者： Galvao, Felipe L. Falcao, Alexandre X. Chowdhury, Ananda S. Univ Estadual Campinas Inst Comp Campinas SP Brazil Jadavpur Univ Dept Elect & Telecommun Engn Kolkata India

ISBN: (纸本)9781538692646

Methods for superpixel segmentation have become very popular in computer vision. Recently, a graph-based framework named ISF (Iterative Spanning Forest) was proposed to obtain connected superpixels (supervoxels in 3D) based on multiple executions of the image Foresting Transform (IFT) algorithm from a given choice of four components: a seed sampling strategy, an adjacency relation, a connectivity function, and a seed recomputation procedure. In this paper, we extend ISF to introduce a unique characteristic among superpixel segmentation methods. Using the new framework, termed as Recursive Iterative Spanning Forest (RISF), one can recursively generate multiple segmentation scales on region adjacency graphs (i.e., a hierarchy of superpixels) without sacrificing the efficiency and effectiveness of ISF. In addition to a hierarchical segmentation, RISF allows a more effective geodesic seed sampling strategy, with no negative impact in the efficiency of the method. For a fixed number of scales using 2D and 3D image datasets, we show that RISF can consistently outperform the most competitive ISF-based methods.

关键词： Forestry image segmentation Vegetation image color analysis Three-dimensional displays Transforms Two dimensional displays

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