These days, there are numerous issues related to copyright protection and ownership identification as a result of the improper use of electronic data. With growing speed of online media, authentication has become a ne...
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We will present our easy-to-use learning suite (i) that supports hands-on experience through physical computing, (ii) uses an easy-to-use visual programming interface, and (iii) relates to authentic real-world applica...
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Classification of 3D objects - the selection of a category in which each object belongs - is of great interest in the field of machine learning. Numerous researchers use deep neural networks to address this problem, a...
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Classification of 3D objects - the selection of a category in which each object belongs - is of great interest in the field of machine learning. Numerous researchers use deep neural networks to address this problem, altering the network architecture and representation of the 3D shape used as an input. To investigate the effectiveness of their approaches, we conduct an extensive survey of existing methods and identify common ideas by which we categorize them into a taxonomy. Second, we evaluate 11 selected classification networks on two 3D object datasets, extending the evaluation to a larger dataset on which most of the selected approaches have not been tested yet. For this, we provide a framework for converting shapes from common 3D mesh formats into formats native to each network, and for training and evaluating different classification approaches on this data. Despite being partially unable to reach the accuracies reported in the original papers, we compare the relative performance of the approaches as well as their performance when changing datasets as the only variable to provide valuable insights into performance on different kinds of data. We make our code available to simplify running training experiments with multiple neural networks with different prerequisites.
Bidirectional reflection distribution function (BRDF) is a function that describes the optical properties of the object surface, which reflects the reflection characteristics of the object surface under different angl...
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Polycube-maps are highly valuable in computer graphics, particularly concerning hexahedral meshes. Currently, the validity of polycube is determined based on Steinitz and Eppstein’s approach, which only addresses 3-c...
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This paper is about the study of computer graphic based on appearance modelling. and. subsurface scattering mainly discussing that the purpose of computer graphics is to make the picture more beautiful and nicer becau...
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The articles in this special section focus on analytic rendering and hardware-accelerated simulation for scientific applications. Data visualization is now one of the cornerstones of data science, turning the abundanc...
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The articles in this special section focus on analytic rendering and hardware-accelerated simulation for scientific applications. Data visualization is now one of the cornerstones of data science, turning the abundance of big data being produced through modern systems into actionable knowledge. Data visualization in the big data era raises the need to co-design and more closely align the underlying data management systems with the user-oriented techniques that state-of-the-art visualization systems now offer. In addition, the tight integration of suitable machine learning approaches with data visualization and their control by users-in-theloop promises to enhance scalability, effectiveness, and adaptivity of the interactive visual data analysis process. This special issue attracted and publishes research work on multidisciplinary research areas from the human–computer interaction, computer graphics, and data management communities.
Visual distortion, known as metamorphopsia, is a serious visual deficit with no effective clinical treatment and which cannot be corrected by traditional optical glasses. In this paper, we introduce a toolkit of appro...
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ISBN:
(纸本)9798400702204
Visual distortion, known as metamorphopsia, is a serious visual deficit with no effective clinical treatment and which cannot be corrected by traditional optical glasses. In this paper, we introduce a toolkit of approaches for digitally mapping and correcting visual distortion, that might eventually be incorporated in a low vision aid VR headset. We describe three different approaches spanning data-driven and generative designs and leveraging either uniocular or binocular cues. We present our proposed demonstrator, our evaluation roadmap, and challenges for the field. Initial tests with simulated data demonstrate the effectiveness of the approach. Once clinically validated, we hope these approaches will enable accurate mapping of visual distortion and eventually lead to the development of 'digital glasses' capable of correcting the effects of metamorphopsia and restoring healthy vision.
Neeharika Adabala, India Florent Lafarge, France Bruno Levy, INRIA, France Liang Lin, Sun Yat-sen University, China Masayuki Nakajima, Japan Bodo Rosenhahn, Leibniz University of Hannover, Germany Jianbin Shen, China ...
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Neeharika Adabala, India Florent Lafarge, France Bruno Levy, INRIA, France Liang Lin, Sun Yat-sen University, China Masayuki Nakajima, Japan Bodo Rosenhahn, Leibniz University of Hannover, Germany Jianbin Shen, China Qixiang Ye, Chinese Academy of Sciences, China The editorial board of the Visual computer is renewed regularly.
Antonio Agudo, CSIC-UPC, Spain Imon Banerjee, Emory University School of Medicine, USA Sebastiano Battiato, Università di Catania, Italy Tolga Birdal, Stanford University, USA Ladislau Boloni, University of Central Florida, USA Zhonggui Chen, Xiamen University, China Sunghyun Cho, POSTEC, South Korea Jan Egger, Graz University of Technology, Austria Antonino Furnari, University of Catania, Italy Zhenhua Guo, Alibaba Group, China Dakai Jin, PAII Inc., USA Stefano Mattoccia, University of Bologna, Italy Tae-Hyun Oh, POSTECH, South Korea Jinshan Pan, Nanjing University of Science and Technology, China Andrea Prati, Università degli Studi di Parma, Italy Jonathan Roberts, Bangor University, UK Thomas Schultz, University of Bonn, Germany Bernie Tiddeman, Aberystwyth University, UK Zhigang Tu, Wuhan University, China Nannan Wang, Xidian University, Xi'an City, China Mingqiang Wei, Nanjing University of Aeronautics and Astronautics, China Yücel Yemez, Koç University, Turkey During 2021, as usual, the journal published a special issue containing the best papers from the computer graphics International Conference (CGI’2021) organized by the computer graphics Society (CGS).
Nadia Magnenat Thalmann Editor-in-Chief The Visual computer Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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