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Randomrewardmechanisms (Loot Boxes): Behavioral Economics As A Regulatory Solution In brazilian Law 17

Randomrewardmechanisms (Loot Boxes): Behavioral Economics As...

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17th International Conference on Interfaces and Human computer Interaction 2023, IHCI 2023, the 17th International Conference on computer graphics, Visualization, computer Vision and image processing 2023, CGVCVIP 2023 and 16th International Conference on Game and Entertainment Technologies 2023, GET 2023

作者： Fantini, Laiane Maris Caetano PUC Minas. Centro DTIBR MG Belo Horizonte Brazil

ISBN: (纸本)9789898704498

the paper seeks to reflect on ways to create an effective regulation by understanding the aspects of random reward mechanisms in video games, also known as loot boxes. Players acquire digital assets of a game through microtransactions, and pays with in-game currency or real money. Among these digital assets, several games also offer loot boxes, which are systems of "surprise boxes" with a certain price but whose reward is unknown to the player (and is only revealed when the box is purchased and opened). A simple way of selling a digital asset has serious implications for players, mainly due to the similarity with gambling in making the reward relegated to chance. Also, adults and children players are encouraged to exhibit addictive behaviors, spending time and money without any control. brazilian law does not have enough apparatus to protect consumers from these practices and banning loot boxes from the market does not seem to be the solution, as similar mechanisms could arise even worse. this way of marketing digital assets hides the real transaction costs and makes consumers make decisions based on heuristics, and that's why the Behavioral Economic theory can offer better solutions to protect players. © 2023 Proceedings of the International Conferences on Interfaces and Human computer Interaction 2023, IHCI 2023;computer graphics, Visualization, computer Vision and image processing 2023, CGVCVIP 2023;and Game and Entertainment Technologies 2023, GET 2023. All rights reserved.

关键词： Human computer interaction

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Reconstruction using surface dedicated tensorial field 16

Reconstruction using surface dedicated tensorial field

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16th brazilian symposium on computer graphics and image processing, SIBGRAPI 2003

作者： Vieira, M.B. Cord, M. Martins, P.P. Philipp-Foliguet, S. Araújo, A.D.A. IMPA - Instituto de Matemática Pura e Aplicada Est. Dona Castorina 110 Rio de JaneiroRJ22460-320 Brazil NPDI/DCC Universidade Federal de Minas Gerais Caixa Postal 702 Belo HorizonteMG30161-970 Brazil Ecole Nationale Supérieure d'Electronique et de Ses Applications 6 av. du Ponceau Cergy Cedex95014 France Centro Tecnológico de Minas Gerais av. José Cândido da Silveira 2000 Belo HorizonteMG31170-000 Brazil

ISBN: (纸本)0769520324

We propose a new strategy to estimate surface normals from sparse data for reconstruction. Our approach is based on tensorial fields morphologically adapted to infer normals forming smooth surfaces. they act as three-dimensional structuring elements for finding precise normals. Robust orientation inference is performed by an enhanced accumulation process using the tensorial fields. the surface dedicated aspects of our propositions are suitable for smooth surface inference from noisy data. We present qualitative and quantitative results to show the behavior of the original methods and ours. A comparative discussion of these results remarks the efficiency of our extensions. © 2003 IEEE.

关键词： image reconstruction

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

作者： Andrade, Natan Faria, Fabio A. Cappabianco, Fabio A. M. Univ Fed Sao Paulo GIBIS Dept Sci & Technol Av Cesare Monsueto Giulio Lattes 1201 BR-12247014 Sao Jose Dos Campos SP Brazil

ISBN: (纸本)9781665423540

Brain image registration fuses and aligns sets of structural or functional images within individual and population studies. the similarity metric is an image registration component used for detecting the same target region in different images. Multi-modal image registration constitutes one of the greatest challenges in medical imaging as it adds even more variability to the tissue and organ appearance, shape, and positioning. this paper contains two contributions to solve this complex problem: (1) we propose a solution to compute the similarity metric based on a deep ensemble method. It combines multiple traditional and deep similarity metrics into a single improved similarity map;(2) we propose novel evaluation metrics to validate the results. Experiment results in the context of T1- and T2-weighted MR images of the human brain show a major improvement to the state-of-the-art, especially in reducing the false-positive region occurrences.

关键词： Measurement image registration Brain Shape Fuses Sociology Statistics

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Presenter-Centric image Collection and Annotation: Enhancing Accessibility for the Visually Impaired 36

Presenter-Centric Image Collection and Annotation: Enhancing...

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

作者： Ferreira, Luisa Fernandes, Daniel Cerqueira, Fabio Ribeiro, Marcos Silva, Michel Univ Fed Vicosa UFV Dept Informat Vicosa MG Brazil Univ Fed Fluminense UFF Dept Prod Engn Petropolis RJ Brazil

ISBN: (纸本)9798350338737;9798350338720

With the recent COVID-19 pandemic, our daily lives and workplace became more dependent on technologies, e.g., the intensive use of video conferences. While a highly connected world enables remote working, it also raises new barriers for an already excluded community, the visually impaired people. Low or no eyesight prevents those people from capturing visual information, which makes it difficult to understand the overall context of a remote presentation. Most Artificial Intelligence methods are specific to sighted-people data domains due to the scarcity of datasets for the visually impaired. In this paper, we propose an approach to collect data automatically and a protocol to annotate this data specifically for this audience, aiming to support the development of Assistive Technology systems. We demonstrate the viability of the proposed methods by creating a dataset and evaluating its quality, diversity, and representativeness through analytical methods and machine learning models.

关键词： COVID-19

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Multi-Object Segmentation by Hierarchical Layered Oriented image Foresting Transform 30

Multi-Object Segmentation by Hierarchical Layered Oriented I...

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

作者： Castaneda Leon, Leissi M. Miranda, Paulo A. V. Univ Sao Paulo Inst Math & Stat Sao Paulo SP Brazil

ISBN: (纸本)9781538622193

this paper introduces a new method for multi-object segmentation in images, named as Hierarchical Layered Oriented image Foresting Transform (HLOIFT). As input, we have an image, a tree of relations between image objects, with the individual high-level priors of each object coded in its nodes, and the objects' seeds. Each node of the tree defines a weighted digraph, named as layer. the layers are then integrated by the geometric interactions, such as inclusion and exclusion relations, extracted from the given tree into a unique weighted digraph, named as hierarchical layered digraph. A single energy optimization is performed in the hierarchical layered weighted digraph by Oriented image Foresting Transform (OIFT) leading to globally optimal results satisfying all the high-level priors. We evaluate our framework in the multi-object segmentation of medical and synthetic images, obtaining results comparable to the state-of-the-art methods, but with low computational complexity. Compared to multi-object segmentation by min-cut/max-flow algorithm, our approach is less restrictive, leading to globally optimal results in more general scenarios.

关键词： image segmentation Transforms Optimization Vegetation Object segmentation Biomedical imaging

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Enhancing brazilian Sign Language Recognition through Skeleton image Representation 37

Enhancing Brazilian Sign Language Recognition through Skelet...

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37th SIBGRAPI Conference on graphics, Patterns and images (SIBGRAPI)

作者： Alves, Carlos Eduardo G. R. Boldt, Francisco de A. Paixao, thiago M. Inst Fed Espirito Santo IFES Vitoria ES Brazil

ISBN: (纸本)9798350376043;9798350376036

Effective communication is paramount for the inclusion of deaf individuals in society. However, persistent communication barriers due to limited Sign Language (SL) knowledge hinder their full participation. In this context, Sign Language Recognition (SLR) systems have been developed to improve communication between signing and non-signing individuals. In particular, there is the problem of recognizing isolated signs (Isolated Sign Language Recognition, ISLR) of great relevance in the development of vision-based SL search engines, learning tools, and translation systems. this work proposes an ISLR approach where body, hands, and facial landmarks are extracted throughout time and encoded as 2-D images. these images are processed by a convolutional neural network, which maps the visual-temporal information into a sign label. Experimental results demonstrate that our method surpassed the state-of-the-art in terms of performance metrics on two widely recognized datasets in brazilian Sign Language (LIBRAS), the primary focus of this study. In addition to being more accurate, our method is more time-efficient and easier to train due to its reliance on a simpler network architecture and solely RGB data as input. Source code and pre-trained models are publicly available at https://***/Dudu197/sign-language-recognition.

关键词： Convolutional neural networks

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Two-stage binary image operator design: An approach based on interaction information

Two-stage binary image operator design: An approach based on...

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20th brazilian symposium on computer graphics and image processing, SIBGRAPI 2007

作者： Santos, Carlos S. Hirata, Nina S. T. Hirata Jr., Roberto Department of Computer Science Institute of Mathematics and Statistics University of Sacombining Double Acute Accento Paulo Rua do Matacombining double acute accento 1010 05508-090 Sacombining double acute accento Paulo Brazil

ISBN: (纸本)0769529968

We address the problem of binary image operator design over large windows by breaking it into two phases. Firstly, we design several operators over small sub-windows of the main window. the outputs of these first level operators are then combined into a global operator. We devise a heuristic, motivated by Information theory, for breaking the main window into sub-windows. Preliminary results show that the proposed scheme improves operator performance over single-level operators. © 2007 IEEE.

关键词： Binary images

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Unsupervised image Segmentation by Oriented image Foresting Transform in Layered Graphs 36

Unsupervised Image Segmentation by Oriented Image Foresting ...

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

作者： Kleine, Felipe A. S. Santos, Luiz F. D. Cappabianco, Fabio A. M. Miranda, Paulo A., V IPT Inst Technol Res State Sao Paulo Sao Paulo Brazil Univ Sao Paulo Inst Math & Stat Sao Paulo SP Brazil Inst Ciencia & Tecnol Sao Jose Dos Campos SP Brazil

ISBN: (纸本)9798350338737;9798350338720

In this work, we address the problem of unsupervised image segmentation, subject to high-level constraints expected for the objects of interest. More specifically, we handle the segmentation of a hierarchy of objects with nested boundaries, each with its own expected boundary polarity constraint. To this end, this work successfully extends Hierarchical Layered Oriented image Foresting Transform (HLOIFT), with the inclusion of nested object relations, to the unsupervised segmentation paradigm. On the other hand, this work can also be seen as an extension of Unsupervised OIFT (UOIFT) to include structural relationships of nested objects. the method is demonstrated in the segmentation of three datasets of colored images with superior performance compared to other existing techniques in graphs, requiring a smaller number of connected partitions to isolate the objects of interest in the images.

关键词： image segmentation

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A New Grammar for Creating Convolutional Neural Networks Applied to Medical image Classification 34

A New Grammar for Creating Convolutional Neural Networks App...

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

作者： da Silva, Cleber A. C. F. Miranda, Pericles B. C. Cordeiro, Filipe R. Fed Rural Univ Pernambuco UFRPE Dept Stat & Informat Recife PE Brazil

ISBN: (纸本)9781665423540

In the last decade, the adoption of Deep Convolutional Neural Networks (CNNs) has been successfully applied to solve computer vision tasks, such as image classification in the medical field. However, the several architectures proposed in the literature are composed of an increasing number of parameters and complexity. therefore, finding the optimal trade-off between accuracy and model complexity for a given data set is challenging. To help the search for these suitable configurations, this work proposes using a new Context-Free Grammar associated with a Multi-Objective Grammatical Evolution Algorithm that generates suitable CNNs for a given image classification problem. In this structure, the new grammar maps every possible search space for the creation of networks. Furthermore, the Multi-Objective Grammatical Evolution Algorithm used optimizes this search taking into account two objective functions: accuracy and F-1-score. Our proposal was used in three medical image datasets from MedMNIST: PathMNIST, OCTMNIST, and OrganMNIST Axial. the results showed that our method generated simpler networks with equal or superior performance from state-of-the-art (more complex) networks and others CNNs also generated by grammatical evolution process.

关键词： Grammatical Evolution Deep Neural Networks Multi-Objective Optimization

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Repairing Non-manifold Boundaries of Segmented Simplicial Meshes 30

Repairing Non-manifold Boundaries of Segmented Simplicial Me...

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

作者： Choque Ramos, Tony L. Cuadros Vargas, Alex J. Univ Catolica San Pablo Arequipa Peru

ISBN: (纸本)9781538622193

A digital image may contain objects that can be made up of multiple regions concerning different material properties, physical or chemical attributes. thus, segmented simplicial meshes with non-manifold boundaries are generated to represent the partitioned regions. We focus on repairing non-manifold boundaries. Current methods modify the topology, geometry or both, using their own data structures. the problem of modifying the topology is that if the mesh has to be post-processed, for instance with the Delaunay refinement, the mesh becomes unsuitable. In this paper, we propose alternatives to repair nonmanifold boundaries of segmented simplicial meshes, among them is the Delaunay based one, we use common data structures and only consider 2 and 3 dimensions. We developed algorithms for this purpose, composed of the following tools: relabeling, point insertion and simulated annealing. these algorithms are applied depending on the targeted contexts, if we want to speed the process, keep as possible the original segmented mesh or keep the number of elements in the mesh.

关键词： Manifolds three-dimensional displays image segmentation Data structures Maintenance engineering Simulated annealing Cavity resonators

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