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检索条件"任意字段=16th Brazilian Symposium on Computer Graphics and Image Processing"

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Object retrieval in image databases using image composition

Object retrieval in image databases using image composition

引用

brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： S. Philipp-Foliguet M. Lekkat Equipes Traitement des Images et du Signal ENSEA UCP Cergy France

We propose an algorithm of image retrieval from a partial request. In order to retrieve images containing a specific object or group of objects, we use an algorithm of inexact graph matching, adapted to adjacency graphs of regions. the number of regions representing the object can be different from an image to the other. the algorithm uses a search tree in which only similar nodes are developed. the adjacency and spatial relationship of regions are used to prune the tree and accelerate the retrieval. the algorithm computes a distance between graphs, allowing to rank images. this distance takes into account both the distance between region features and the relative position of regions.

关键词： Information retrieval image retrieval image databases image segmentation Topology Tree graphs Spatial databases Visual system Spatial resolution Acceleration

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New hierarchy-based segmentation layer: towards automatic marker proposal 34

New hierarchy-based segmentation layer: towards automatic ma...

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34th SIBGRAPI Conference on graphics, Patterns and images (SIBGRAPI)

作者： da Fonseca, Gabriel Barbosa Negrel, Romain Perret, Benjamin Cousty, Jean Guimaraes, Silvio Jamil F. Pontificia Univ Catolica Minas Gerais Lab Image & Multimedia Data Sci BR-31980110 Belo Horizonte MG Brazil Univ Gustave Eiffel LIGM CNRS ESIEE Paris F-77454 Marne La Vallee France Univ Gustave Eiffel ESIEE Paris Champs Sur Marne France

ISBN: (纸本)9781665423540

image segmentation is an ill-posed problem by definition, as it is not always possible to automatically select which object appearing in an image is the object of interest. To deal with this issue, prior knowledge in the form of human-given markers can be included in the segmentation pipeline. Even though user interaction can drastically improve segmentation results, it is an expensive resource, and finding ways to reduce human effort on an interactive segmentation loop is of great interest. In this work, we propose a new segmentation layer to be used with deep neural networks, which allows us to create and train in an end-to-end fashion a marker creation network. To train the network, we propose a loss function composed of: a segmentation loss using the proposed differentiable segmentation layer;and a set of regularization functions that enforce the desired characteristics on the produced markers. We showed that by using the proposed layer and loss function, we can train the network to automatically generate markers that recover a good segmentation and have desirable shape characteristics. this behavior is observed on the training dataset, as well as on four unseen datasets.

关键词： Training Deep learning image segmentation Shape Pipelines Proposals

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Multiscale image segmentation using wavelets and watersheds

Multiscale image segmentation using wavelets and watersheds

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： C.R. Jung Centro de Ciencias Exatas e Tecnológicas UNISINOS Universidade do Vale do Rio dos Sinos Rio Grande do Sul Brazil

We propose a new multiscale segmentation technique based on wavelet decompositions and watersheds. the wavelet transform is applied to the image, producing detail and approximation coefficients. the watershed is applied to the approximation image at a certain resolution 2/sup J/, and projected up to higher resolutions using the inverse wavelet transform. At lower resolutions, the segmentation captures large relevant objects, while at higher resolution more details are obtained. Since downsizing is inherent to the wavelet transform, watershed segmentation is applied to a smaller image, demanding less computational time. the proposed technique appears to be robust for noisy images, even when the amount of noise is very large.

关键词： image segmentation image resolution Wavelet transforms Frequency image edge detection Shape measurement Filters Energy resolution Position measurement Size measurement

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A new method for modeling clouds combining procedural and implicit models 16

A new method for modeling clouds combining procedural and im...

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16th brazilian symposium on computer Games and Digital Entertainment (SBGames)

作者： Montenegro, Anselmo Baptista, Icaro Clua, Esteban Dembogurski, Bruno Univ Fed Fluminense Dept Ciencia Comp Niteroi RJ Brazil Univ Fed Rural Rio De Janeiro Dept Ciencia Comp Rio De Janeiro Brazil

ISBN: (纸本)9781538648469

Cloud models are important components in 3D open environment games and virtual reality applications. In the literature, different approaches have been proposed to solve the problem of modeling the complex geometry and texture of clouds including physical simulation, photo-based modeling and a combination of implicit modeling with procedural techniques. the latter is simple and produces satisfactory results and can be also done in realtime. Nevertheless, it is still difficult to produce the desired results by combining implicit modeling with procedural techniques. the reasons for this limitation are twofold. First, the parameters are not intuitive and intricately coupled with each other. the second reason is that it is hard to combine the overall shape defined by the implicit model with the details generated by the procedural models in a smooth and localized way. In this work, we propose a new way of modeling clouds by combining volumetric implicit modeling with procedural noise techniques. Differently from previous works, the details produced by noise are attached to each implicit primitive independently, in different scales, before they are smoothly blended. this provides a greater level of control in the process of designing and modeling the clouds. By implementing our technique in GPUs it is possible to change the parameters and the blending of primitives in realtime and observe immediately the produced results. this interactive behavior enables the modeler to more easily build and experiment different versions of his ideas. Although we applied this technique to cloud modeling we show that the same approach can be useful for modeling many natural objects as rocks, terrain and planet shapes, among others.

关键词： Modeling of Clouds Procedural Modeling Implicit Modeling GPU processing

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Towards a Simple and Efficient Object-based Superpixel Delineation Framework 34

Towards a Simple and Efficient Object-based Superpixel Delin...

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34th SIBGRAPI Conference on graphics, Patterns and images (SIBGRAPI)

作者： Belem, Felipe C. Perret, Benjamin Cousty, Jean Guimaraes, Silvio J. F. Falcao, Alexandre X. Univ Estadual Campinas Inst Comp LIDS Sao Paulo Brazil Univ Gustave Eiffel LIGM CNRS ESIEE Paris Marne La Vallee France Pontificia Univ Catolica Minas Gerais IMSci Belo Horizonte MG Brazil

ISBN: (纸本)9781665423540

Superpixel segmentation methods are widely used in computer vision applications due to their properties in border delineation. these methods do not usually take into account any prior object information. Although there are a few exceptions, such methods significantly rely on the quality of the object information provided and present high computational cost in most practical cases. Inspired by such approaches, we propose Object-based Dynamic and Iterative Spanning Forest (ODISF), a novel object-based superpixel segmentation framework to effectively exploit prior object information while being robust to the quality of that information. ODISF consists of three independent steps: (i) seed oversampling;(ii) dynamic path-based superpixel generation;and (iii) object-based seed removal. After (i), steps (ii) and (iii) are repeated until the desired number of superpixels is finally reached. Experimental results show that ODISF can surpass state-of-the-art methods according to several metrics, while being significantly faster than its object-based counterparts.

关键词： Measurement graphics computer vision Forestry Computational efficiency Iterative methods

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Improving Transferability of Domain Adaptation Networks through Domain Alignment Layers 34

Improving Transferability of Domain Adaptation Networks Thro...

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34th SIBGRAPI Conference on graphics, Patterns and images (SIBGRAPI)

作者： Silva, Lucas F. A. Pedronette, Daniel C. G. Faria, Fabio A. Papa, Joao P. Almeida, Jurandy Univ Fed Sao Paulo UNIFESP Inst Ciencia & Tecnol Sao Jose Dos Campos SP Brazil Sao Paulo State Univ UNESP Dept Stat Appl Math & Comp Rio Claro SP Brazil Sao Paulo State Univ UNESP Dept Comp Bauru SP Brazil

ISBN: (纸本)9781665423540

Deep learning (DL) has been the primary approach used in various computer vision tasks due to its relevant results achieved on many tasks. However, on real-world scenarios with partially or no labeled data, DL methods are also prone to the well-known domain shift problem. Multi-source unsupervised domain adaptation (MSDA) aims at learning a predictor for an unlabeled domain by assigning weak knowledge from a bag of source models. However, most works conduct domain adaptation leveraging only the extracted features and reducing their domain shift from the perspective of loss function designs. In this paper, we argue that it is not sufficient to handle domain shift only based on domain-level features, but it is also essential to align such information on the feature space. Unlike previous works, we focus on the network design and propose to embed Multi-Source version of DomaIn Alignment Layers (MS-DIAL) at different levels of the predictor. these layers are designed to match the feature distributions between different domains and can be easily applied to various MSDA methods. To show the robustness of our approach, we conducted an extensive experimental evaluation considering two challenging scenarios: digit recognition and object classification. the experimental results indicated that our approach can improve state-of-the-art MSDA methods, yielding relative gains of up to +30.64% on their classification accuracies.

关键词： graphics Deep learning computer vision Adaptation models Predictive models Feature extraction Robustness

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Exploration and search-by-similarity in CBIR

Exploration and search-by-similarity in CBIR

引用

brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： M. Cord J. Fournier S. Philipp-Foliguet ETIS (CNRS UMR-8051) University of Cergy-Pontoise ENSEA Cergy-Pontoise France

We deal with content-based image indexing and category retrieval in general databases. When large categories are searched, systems must explore the database. We introduce an interactive retrieval strategy designed for database exploration. the technique is based on a compound query and a dedicated similarity function. the usual strategy based on a similarity score ranking is replaced by a stochastic image selection process. A competition between feature spaces for the similarity measure refinement is also included in the strategy. A quality assessment is realized on a general database of 6000 images in order to illustrate and validate our approach.

关键词： image databases image retrieval Spatial databases Information retrieval Content based retrieval Stochastic processes Data mining Feedback Indexing Quality assessment

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Hierarchical skeleton-based implicit model

Hierarchical skeleton-based implicit model

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Proceedings of the 1997 10th brazilian symposium of computer Graphic and image processing, SIBGRAPI 97

作者： Malheiros, Marcelo De Gomensoro Wu, Shin-Ting Universidade Estadual de Campinas Campinas Brazil

Implicit modeling is a recent trend in computer graphics and a variety of skeleton-based models has been proposed. In this paper we present a hierarchical framework that can encompass a wide range of these variants, providing a more flexible way for defining the shape of implicit objects. We also derive a new decay function, which is computationally cheap.

关键词： computer graphics

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DRIFT: A visual analytic tool for scientific literature exploration based on textual and image content 34

DRIFT: A visual analytic tool for scientific literature expl...

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34th SIBGRAPI Conference on graphics, Patterns and images (SIBGRAPI)

作者： Pocco, Ximena Poco, Jorge Viana, Matheus de Paula, Rogerio Nonato, Luis G. Gomez-Nieto, Erick Univ Catolica San Pablo Dept Comp Sci Arequipa Peru Getulio Vargas Fdn Sch Appl Math Rio De Janeiro Brazil IBM Res Sao Paulo Brazil Univ Sao Paulo ICMC Sao Carlos Brazil

ISBN: (纸本)9781665423540

Exploring digital libraries of scientific articles is an essential task for any research community. the typical approach is to query the articles' data based on keywords and manually inspect the resulting list of documents to identify which papers are of interest. Besides being time-consuming, such a manual inspection is quite limited, as it can hardly provide an overview of articles with similar topics or subjects. Moreover, accomplishing queries based on content other than keywords is rarely doable, impairing finding documents with similar images. In this paper, we propose a visual analytic methodology for exploring and analyzing scientific document collections that consider the content of scientific documents, including images. the proposed approach relies on a combination of Content-Based image Retrieval (CBIR) and multidimensional projection to map the documents to a visual space based on their similarity, thus enabling an interactive exploration. Additionally, we enable visual resources to display complementary information on selected documents that uncover hidden patterns and semantic relations. We show the effectiveness of our methodology through two case studies and a user evaluation, which attest to the usefulness of the proposed framework in exploring scientific document collections.

关键词： Visual analytics Semantics image retrieval Manuals Inspection Libraries Task analysis

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Moving least squares multiresolution surface approximation

Moving least squares multiresolution surface approximation

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： B. Mederos L. Velho L.H. De Figueiredo IMPA-Instituto de Matemáica Pura e Aplicada Rio de Janeiro Brazil IMPA-Instituto de Matemática Pura e Aplicada Rio de Janeiro RJ Brazil

We describe a new method for surface reconstruction based on unorganized point clouds without normals. We also present a new algorithm for refining the initial triangulation. the output of the method is a refined tria... 详细信息

关键词： Least squares approximation Surface reconstruction Least squares methods three-dimensional displays Multiresolution analysis Scattering Computational geometry image reconstruction Greedy algorithms Clustering algorithms

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