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"abstract": "With the development of artificial intelligence technology, it is possible to automatically colorize the hand drawn sketch by machine. Researchers have conducted in-depth and meticulous study on hand-drawn manuscript recognition, generation, and retrieval. For the emotion-based line art colorization, facial expression should be also extracted from the image itself. To solve the recognition and colorization problem, this paper has proposed an algorithm with the DenseNet network for emotional recognition of anime faces and performed a two-stage interactive coloring method in view of superpixel color analysis features. Among them, the superpixel color analysis technology used a simple linear iterative clustering of SLIC algorithm. According to the experiment, the prompt color information of corresponding position could be generated through the emotion recognition result. After the prediction of superpixel color analysis by GAN (generative adversarial network), the original cartoon image could be rendered with suitable color scheme. The visualization results proved that our algorithm proposed would effectively realize the emotion-based line art colorization of high interactivity and reasonable color distribution.",
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"content": "With the development of artificial intelligence technology, it is possible to automatically colorize the hand drawn sketch by machine. Researchers have conducted in-depth and meticulous study on hand-drawn manuscript recognition, generation, and retrieval. For the emotion-based line art colorization, facial expression should be also extracted from the image itself. To solve the recognition and colorization problem, this paper has proposed an algorithm with the DenseNet network for emotional recognition of anime faces and performed a two-stage interactive coloring method in view of superpixel color analysis features. Among them, the superpixel color analysis technology used a simple linear iterative clustering of SLIC algorithm. According to the experiment, the prompt color information of corresponding position could be generated through the emotion recognition result. After the prediction of superpixel color analysis by GAN (generative adversarial network), the original cartoon image could be rendered with suitable color scheme. The visualization results proved that our algorithm proposed would effectively realize the emotion-based line art colorization of high interactivity and reasonable color distribution.",
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"fullName": "Zhi-bin Su",
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"abstract": "Popular social media platforms could rapidly propagate vital information over social networks among a significant number of people. In this work we present D-Map (Diffusion Map), a novel visualization method to support exploration and analysis of social behaviors during such information diffusion and propagation on typical social media through a map metaphor. In D-Map, users who participated in reposting (i.e., resending a message initially posted by others) one central user's posts (i.e., a series of original tweets) are collected and mapped to a hexagonal grid based on their behavior similarities and in chronological order of the repostings. With additional interaction and linking, D-Map is capable of providing visual portraits of the influential users and describing their social behaviors. A comprehensive visual analysis system is developed to support interactive exploration with D-Map. We evaluate our work with real world social media data and find interesting patterns among users. Key players, important information diffusion paths, and interactions among social communities can be identified.",
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"content": "Popular social media platforms could rapidly propagate vital information over social networks among a significant number of people. In this work we present D-Map (Diffusion Map), a novel visualization method to support exploration and analysis of social behaviors during such information diffusion and propagation on typical social media through a map metaphor. In D-Map, users who participated in reposting (i.e., resending a message initially posted by others) one central user's posts (i.e., a series of original tweets) are collected and mapped to a hexagonal grid based on their behavior similarities and in chronological order of the repostings. With additional interaction and linking, D-Map is capable of providing visual portraits of the influential users and describing their social behaviors. A comprehensive visual analysis system is developed to support interactive exploration with D-Map. We evaluate our work with real world social media data and find interesting patterns among users. Key players, important information diffusion paths, and interactions among social communities can be identified.",
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"affiliation": "Southwest University of Science and Technology, China",
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"abstract": "Nowadays, in the world of limited attention, the techniques that maximize the spread of social influence are more than welcomed. Companies try to maximize their profits on sales by providing customers with free samples believing in the power of word-of-mouth marketing, governments and non-governmental organizations often want to introduce positive changes in the society by appropriately selecting individuals or election candidates want to spend least budget yet still win the election. In this work we propose the use of evolutionary algorithm as a mean for selecting seeds in social networks. By framing the problem as genetic algorithm challenge we show that it is possible to outperform well-known greedy algorithm in the problem of influence maximization for the linear threshold model in both: quality (up to 16% better) and efficiency (up to 35 times faster). We implemented these two algorithms by using GPGPU approach showing that also the evolutionary algorithm can benefit from GPU acceleration making it efficient and scaling better than the greedy algorithm. As the experiments conducted by using three real world datasets reveal, the evolutionary approach proposed in this paper outperforms the greedy algorithm in terms of the outcome and it also scales much better than the greedy algorithm when the network size is increasing. The only drawback in the GPGPU approach so far is the maximum size of the network that can be processed — it is limited by the memory of the GPU card. We believe that by showing the superiority of the evolutionary approach over the greedy algorithm, we will motivate the scientific community to look for an idea to overcome this limitation of the GPU approach — we also suggest one of the possible paths to explore. Since the proposed approach is based only on topological features of the network, not on the attributes of nodes, the applications of it are broader than the ones that are dataset-specific.",
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"content": "Nowadays, in the world of limited attention, the techniques that maximize the spread of social influence are more than welcomed. Companies try to maximize their profits on sales by providing customers with free samples believing in the power of word-of-mouth marketing, governments and non-governmental organizations often want to introduce positive changes in the society by appropriately selecting individuals or election candidates want to spend least budget yet still win the election. In this work we propose the use of evolutionary algorithm as a mean for selecting seeds in social networks. By framing the problem as genetic algorithm challenge we show that it is possible to outperform well-known greedy algorithm in the problem of influence maximization for the linear threshold model in both: quality (up to 16% better) and efficiency (up to 35 times faster). We implemented these two algorithms by using GPGPU approach showing that also the evolutionary algorithm can benefit from GPU acceleration making it efficient and scaling better than the greedy algorithm. As the experiments conducted by using three real world datasets reveal, the evolutionary approach proposed in this paper outperforms the greedy algorithm in terms of the outcome and it also scales much better than the greedy algorithm when the network size is increasing. The only drawback in the GPGPU approach so far is the maximum size of the network that can be processed — it is limited by the memory of the GPU card. We believe that by showing the superiority of the evolutionary approach over the greedy algorithm, we will motivate the scientific community to look for an idea to overcome this limitation of the GPU approach — we also suggest one of the possible paths to explore. Since the proposed approach is based only on topological features of the network, not on the attributes of nodes, the applications of it are broader than the ones that are dataset-specific.",
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"normalizedAbstract": "Nowadays, in the world of limited attention, the techniques that maximize the spread of social influence are more than welcomed. Companies try to maximize their profits on sales by providing customers with free samples believing in the power of word-of-mouth marketing, governments and non-governmental organizations often want to introduce positive changes in the society by appropriately selecting individuals or election candidates want to spend least budget yet still win the election. In this work we propose the use of evolutionary algorithm as a mean for selecting seeds in social networks. By framing the problem as genetic algorithm challenge we show that it is possible to outperform well-known greedy algorithm in the problem of influence maximization for the linear threshold model in both: quality (up to 16% better) and efficiency (up to 35 times faster). We implemented these two algorithms by using GPGPU approach showing that also the evolutionary algorithm can benefit from GPU acceleration making it efficient and scaling better than the greedy algorithm. As the experiments conducted by using three real world datasets reveal, the evolutionary approach proposed in this paper outperforms the greedy algorithm in terms of the outcome and it also scales much better than the greedy algorithm when the network size is increasing. The only drawback in the GPGPU approach so far is the maximum size of the network that can be processed — it is limited by the memory of the GPU card. We believe that by showing the superiority of the evolutionary approach over the greedy algorithm, we will motivate the scientific community to look for an idea to overcome this limitation of the GPU approach — we also suggest one of the possible paths to explore. Since the proposed approach is based only on topological features of the network, not on the attributes of nodes, the applications of it are broader than the ones that are dataset-specific.",
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"title": "Ranking Twitter Influence by Combining Network Centrality and Influence Observables in an Evolutionary Model",
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"abstract": "Influential agents in networks play a pivotal role in information diffusion. Influence may rise or fall quickly over time and thus capturing this evolution of influence is of benefit to a varied number of application domains such as: digital marketing, counter-terrorism or policing. In this paper we investigate the influence of users in programming communities on Twitter. We propose a new model for capturing both time-invariant influence and also temporal influence. The unified model is a combination of network topological methods and observation of influence-relevant events in the network. We provide an application of Hidden Markov Models (HMM) for capturing this effect on the network. There are many possible combinations of influence factors, hence we required a ground-truth for model configuration. We performed a primary survey of our population users to elicit their views on influential users. The survey allowed us to validate the results of our classifier. We introduce a novel reward-based transformation to the Viterbi path of the observed sequences which provides an overall ranking for users. Our results show an improvement in ranking accuracy over using solely topology-based methods for the particular area of interest we sampled. Utilising the evolutionary aspect of the HMM we attempt to predict future states using current evidence. Our prediction algorithm significantly outperforms a collection of naive models, especially in the short term (1-3 weeks).",
"abstracts": [
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"content": "Influential agents in networks play a pivotal role in information diffusion. Influence may rise or fall quickly over time and thus capturing this evolution of influence is of benefit to a varied number of application domains such as: digital marketing, counter-terrorism or policing. In this paper we investigate the influence of users in programming communities on Twitter. We propose a new model for capturing both time-invariant influence and also temporal influence. The unified model is a combination of network topological methods and observation of influence-relevant events in the network. We provide an application of Hidden Markov Models (HMM) for capturing this effect on the network. There are many possible combinations of influence factors, hence we required a ground-truth for model configuration. We performed a primary survey of our population users to elicit their views on influential users. The survey allowed us to validate the results of our classifier. We introduce a novel reward-based transformation to the Viterbi path of the observed sequences which provides an overall ranking for users. Our results show an improvement in ranking accuracy over using solely topology-based methods for the particular area of interest we sampled. Utilising the evolutionary aspect of the HMM we attempt to predict future states using current evidence. Our prediction algorithm significantly outperforms a collection of naive models, especially in the short term (1-3 weeks).",
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"title": "Pseudo Depth Maps for RGB-D SLAM",
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"abstract": "In visual SLAM, RGB-D cameras can actively obtain pixel depth information but are expensive and unsuitable for outdoor use. In contrast, monocular depth estimation is relatively inexpensive and more readily available. There have been some systems that fuse monocular depth estimation with SLAM algorithms, but no method that can directly generate depth maps has been tested with experiments. We propose that using monocular depth estimation results can generate 16-bit pseudo depth maps, which can be combined with monocular images as pseudo RGB-D. The relevant camera parameters can be configured according to the general RGB-D camera SLAM requirements. Experiments with Monodepth2 and ORB-SLAM3 on the KITTI dataset demonstrate that pseudo RGB-D can achieve as satisfactory results in SLAM as in stereo computation. The research paves the way for researchers can quickly examine monocular depth estimation results in more SLAM frameworks, reducing the cost of testing new depth monocular estimation frameworks.",
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"content": "In visual SLAM, RGB-D cameras can actively obtain pixel depth information but are expensive and unsuitable for outdoor use. In contrast, monocular depth estimation is relatively inexpensive and more readily available. There have been some systems that fuse monocular depth estimation with SLAM algorithms, but no method that can directly generate depth maps has been tested with experiments. We propose that using monocular depth estimation results can generate 16-bit pseudo depth maps, which can be combined with monocular images as pseudo RGB-D. The relevant camera parameters can be configured according to the general RGB-D camera SLAM requirements. Experiments with Monodepth2 and ORB-SLAM3 on the KITTI dataset demonstrate that pseudo RGB-D can achieve as satisfactory results in SLAM as in stereo computation. The research paves the way for researchers can quickly examine monocular depth estimation results in more SLAM frameworks, reducing the cost of testing new depth monocular estimation frameworks.",
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"abstract": "Because of all kinds of factors, it is very difficult to achieve coherent sampling and integrated-cycle truncation when power grid harmonics are analyzed. But there inevitably exists spectral leakage when Fourier transform is directly adopted in incoherent sampling mode, and the accuracy of harmonic analysis will be seriously affected. To reduce spectral leakage, it’s a very important measure to weight the sampling data with appropriate window, and combined cosine windows are a series of useful windows for power grid harmonic analysis. Its coefficients are worth of being optimized so as to more notably reduce spectral leakage. To aim at these things, this paper puts forward general principles to optimize combined cosine windows, and deduces the optimized combined cosine windows with maximum side lobe decay. In the incoherent sampling mode, these optimized windows can make side lobes decay with the maximum rate, so they can significantly reduce spectral leakage and can help to realize high-precision power grid harmonics measurement and analysis.",
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"content": "Because of all kinds of factors, it is very difficult to achieve coherent sampling and integrated-cycle truncation when power grid harmonics are analyzed. But there inevitably exists spectral leakage when Fourier transform is directly adopted in incoherent sampling mode, and the accuracy of harmonic analysis will be seriously affected. To reduce spectral leakage, it’s a very important measure to weight the sampling data with appropriate window, and combined cosine windows are a series of useful windows for power grid harmonic analysis. Its coefficients are worth of being optimized so as to more notably reduce spectral leakage. To aim at these things, this paper puts forward general principles to optimize combined cosine windows, and deduces the optimized combined cosine windows with maximum side lobe decay. In the incoherent sampling mode, these optimized windows can make side lobes decay with the maximum rate, so they can significantly reduce spectral leakage and can help to realize high-precision power grid harmonics measurement and analysis.",
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"abstract": "We propose a method to derive shading by referring to an unspecified object to synthesize CG objects realistically into an actual scene. Since our method does not require specific light probes and can be implemented with a commercial RGB + depth sensor, it is applicable to consumer environments. The method conducts spherical harmonic (SH) basis functions regression against luminance of the reference object on the basis of its surface normal. The regression is done along with regularization that constrains the ratios of weights of SH basis functions. The regularization we force is shown to be effective in eliminating ringing artifacts of derived shading. Our method should also be robust to the changing of reference objects because it may refer to various objects. Hence, we evaluated our derived shading with a perceptual indication and showed our method is able to robustly derive perceptually diffuse shading regardless of the reference object's specular reflectance property.",
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"abstract": "Traditional intrinsic image decomposition focuses on decomposing images into reflectance and shading, leaving surfaces normals and lighting entangled in shading. In this work, we propose a Global-Local Spherical Harmonics (GLoSH) lighting model to improve the lighting component, and jointly predict reflectance and surface normals. The global SH models the holistic lighting while local SH account for the spatial variation of lighting. Also, a novel non-negative lighting constraint is proposed to encourage the estimated SH to be physically meaningful. To seamlessly reflect the GLoSH model, we design a coarse-to-fine network structure. The coarse network predicts global SH, reflectance and normals, and the fine network predicts their local residuals. Lacking labels for reflectance and lighting, we apply synthetic data for model pre-training and fine-tune the model with real data in a self-supervised way. Compared to the state-of-the-art methods only targeting normals or reflectance and shading, our method recovers all components and achieves consistently better results on three real datasets, IIW, SAW and NYUv2.",
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"content": "Traditional intrinsic image decomposition focuses on decomposing images into reflectance and shading, leaving surfaces normals and lighting entangled in shading. In this work, we propose a Global-Local Spherical Harmonics (GLoSH) lighting model to improve the lighting component, and jointly predict reflectance and surface normals. The global SH models the holistic lighting while local SH account for the spatial variation of lighting. Also, a novel non-negative lighting constraint is proposed to encourage the estimated SH to be physically meaningful. To seamlessly reflect the GLoSH model, we design a coarse-to-fine network structure. The coarse network predicts global SH, reflectance and normals, and the fine network predicts their local residuals. Lacking labels for reflectance and lighting, we apply synthetic data for model pre-training and fine-tune the model with real data in a self-supervised way. Compared to the state-of-the-art methods only targeting normals or reflectance and shading, our method recovers all components and achieves consistently better results on three real datasets, IIW, SAW and NYUv2.",
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"abstract": "The world is at the intersection of new scientific and technological revolution and industrial change. With the continuous integration of informatization and industrialization, 3D printing technology is indispensable for the fourth industrial revolution. With the continuous development of digital technology, the speed of 3D printing technology into the construction field is accelerating. This paper introduces the principle of 3D printing, combined with its main technology, through the analysis of the pain points of the traditional construction industry, prospects the broad prospects of integrating 3D printing technology into the construction field, and provides reference for the researchers of 3D architectural printing technology in the next step.",
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"affiliation": "University of Jinan,School of Mechanical Engineering,Jinan,China",
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"affiliation": "Dalian University of Technology,Dalian,China",
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"affiliation": "Dalian University of Technology,Dalian,China",
"fullName": "Bin Liu",
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{
"affiliation": "Dalian University of Technology,Dalian,China",
"fullName": "Zhongxuan Luo",
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"content": "Terrorist attacks are on the rise in the last few decades. As we look for alternative methods to address this problem, Social Network Analysis (SNA) offers promising techniques among which visual analytics combines the best of statistical analysis with human n ability to visually recognize hidden patterns and trends in terrorist events and networks. In this paper, we present our work on visual analytics of terrorism in India. Since structured data is not readily available for such analysis, we show how data extracted from online news articles and tweets can be integrated with the Global Terrorism Database (GTD) to produce promising results.",
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"abstracts": [
{
"abstractType": "Regular",
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"__typename": "ArticleAbstractType"
}
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"fno": "58970028",
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"Cloth Modeling",
"Wrinkle Modeling",
"Deformable Models"
],
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{
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{
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{
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"abstract": "This paper presents a novel method for cortical surface atlasing. Group-wise registration is performed through a discrete optimisation framework that seeks to simultaneously improve pairwise correspondences between surface feature sets, whilst minimising a global cost relating to the rank of the feature matrix. It is assumed that when fully aligned, features will be highly linearly correlated, and thus have low rank. The framework is regularised through use of multi-resolution control point grids and higher-order smoothness terms, calculated by considering deformation strain for displacements of triplets of points. Accordingly the discrete framework is solved through high-order clique reduction. The framework is tested on cortical folding based alignment, using data from the Human Connectome Project. Preliminary results indicate that group-wise alignment improves folding correspondences, relative to registration between all pair-wise combinations, and registration to a global average template.",
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{
"abstractType": "Regular",
"content": "This paper presents a novel method for cortical surface atlasing. Group-wise registration is performed through a discrete optimisation framework that seeks to simultaneously improve pairwise correspondences between surface feature sets, whilst minimising a global cost relating to the rank of the feature matrix. It is assumed that when fully aligned, features will be highly linearly correlated, and thus have low rank. The framework is regularised through use of multi-resolution control point grids and higher-order smoothness terms, calculated by considering deformation strain for displacements of triplets of points. Accordingly the discrete framework is solved through high-order clique reduction. The framework is tested on cortical folding based alignment, using data from the Human Connectome Project. Preliminary results indicate that group-wise alignment improves folding correspondences, relative to registration between all pair-wise combinations, and registration to a global average template.",
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"abstractUrl": "/proceedings-article/icpr/2014/5209c143/12OmNs59JTf",
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"id": "proceedings/cvpr/2009/3992/0/05206560",
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"abstractUrl": "/proceedings-article/cvpr/2009/05206560/12OmNvrvjdE",
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"abstractUrl": "/proceedings-article/iccv/2007/04409137/12OmNzkuKCR",
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"doi": null,
"abstractUrl": "/proceedings-article/wacv/2020/09093533/1jPbs0rPdC0",
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"Linear Gradient Domain Technique",
"Laplacian Coordinates",
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"Deformable Models",
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"Mathematical Model",
"Three Dimensional Displays",
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"affiliation": "Zhejiang University, China",
"fullName": "Qiuer Xu",
"givenName": null,
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{
"affiliation": "Zhejiang University, China",
"fullName": "Xiuzi Ye",
"givenName": null,
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{
"affiliation": "Zhejiang University, China",
"fullName": "SanYuan Zhang",
"givenName": null,
"surname": "SanYuan Zhang",
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{
"affiliation": "Zhejiang University, China",
"fullName": "Yin Zhang",
"givenName": null,
"surname": "Yin Zhang",
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"id": "proceedings/wacv/2018/4886/0/488601a876",
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"doi": null,
"abstractUrl": "/proceedings-article/wacv/2018/488601a876/12OmNAOKnQh",
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"id": "proceedings/wacv/2018/4886/0",
"title": "2018 IEEE Winter Conference on Applications of Computer Vision (WACV)",
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"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2009/4442/0/05457440",
"title": "Iterative mesh deformation for dense surface tracking",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2009/05457440/12OmNAkWvJ9",
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"id": "proceedings/iccvw/2009/4442/0",
"title": "2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops",
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"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvmp/2009/3893/0/3893a061",
"title": "Skeleton Driven Laplacian Volumetric Deformation",
"doi": null,
"abstractUrl": "/proceedings-article/cvmp/2009/3893a061/12OmNAle6xC",
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"id": "proceedings/cvmp/2009/3893/0",
"title": "2009 Conference for Visual Media Production",
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"__typename": "RecommendedArticleType"
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{
"id": "proceedings/cadgraphics/2011/4497/0/4497a306",
"title": "Lattice-Based Skinning and Deformation for Real-Time Skeleton-Driven Animation",
"doi": null,
"abstractUrl": "/proceedings-article/cadgraphics/2011/4497a306/12OmNBEGYGs",
"parentPublication": {
"id": "proceedings/cadgraphics/2011/4497/0",
"title": "Computer-Aided Design and Computer Graphics, International Conference on",
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"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icvrv/2014/6854/0/6854a058",
"title": "Animation of Refitted 3D Garment Models for Reshaped Bodies",
"doi": null,
"abstractUrl": "/proceedings-article/icvrv/2014/6854a058/12OmNvAiSyg",
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"id": "proceedings/icvrv/2014/6854/0",
"title": "2014 International Conference on Virtual Reality and Visualization (ICVRV)",
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},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isise/2010/4360/0/4360a202",
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"abstract": "Recently a number of affordable game controllers have been adopted by virtual reality (VR) researchers [1][4]. We present a video1 of a VR demo called TurboTuscany, where we employ such controllers; our demo combines a Kinect controlled full body avatar with Oculus Rift head-mounted-display [2]. We implemented three positional head tracking schemes that use Kinect, Razer Hydra, and PlayStation (PS) Move controllers. In the demo the Kinect tracked avatar can be used to climb ladders, play with soccer balls, and otherwise move or interact with physically simulated objects. PS Move or Razer Hydra controller is used to control locomotion, and for selecting and manipulating objects. Our subjective experience is that the best head tracking immersion is achieved by using Kinect together with PS Move, as the latter is more accurate and responsive while having a large tracking volume. We also noticed that Oculus Rift's orientation tracking has less latency than any of the positional trackers that we used, while Razer Hydra has less latency than PS Move, and Kinect has the largest latency. Besides positional tracking, our demo uses these three trackers to correct the yaw drift of Oculus Rift. TurboTuscany was developed by using our RUIS toolkit, which is a software platform for VR application development [3]. The demo and RUIS toolkit can be downloaded online2.",
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"abstract": "This paper debates the necessity of implementing Virtual Reality Technology as a training tool within Lean Manufacturing Environments (LME). The topic for discussion surrounding this area is the need for a user friendly package that utilizes game and advanced Virtual Reality (VR) Technology to encompass the principles of the Lean approach to manufacturing. Fundamental principles adopted by video game developers attempting to immerse the user could provide a key, through allowing for a fully immersive manufacturing simulation software package. The implementation of VR and training software that would not only teach, but also showcase new technology and show its relevance in a manufacturing system. As a result the use of Lean philosophy acts as a conduit in the implementation of the VR software in adaptable modern manufacturing. Literature within Lean Manufacturing and Video Game Development Immersion Methodologies allow for a juxtaposition between the two, through promoting the validity of novel simulation training techniques. Evaluating case studies of Lean Manufacturing applications will ascertain the need for innovative adaptations, by determining whether solutions could be further improved by latest technological advancements. This paper critically appraises gaming technology and its evolution towards sophisticated design solutions. Learning theories adopted through gaming reveal new approaches to motivational drivers in developing necessary skill sets for modern workforces. Studies surrounding objective based instructional learning highlight rarely acknowledged fields in manufacturing simulation testing. Project Sponsor: Nottingham Trent University & PepsiCo The simulation software is to be built using Unity3D with scripting in C# and Java Script which emulates running of a manufacturing cell within a Lean environment. Its purpose is to train and educate personnel through simulating a functioning manufacturing cell. The software displays potential Lean wastes and problems such as bottle necking. It is imperative to the development of modern manufacturing environments that new simulation techniques in educating workforces, creating prototypes and testing are embraced. Currently only the latter two developments are predominantly created in unison. In Lean, this is wasteful in terms of transport and skill if these are not performed in-house. The need for a more user friendly and intuitive simulation experience requires clarity for potential manufacturers in order to adopt this methodology. Not enough varied Lean manufacturing companies embody Lean principles on a computational software level and as a result could potentially leave entire generations without modern manufacturing skill sets. The concept of VR used in modern Manufacturing Simulation Software (MSS) can be utilised to dispel any belief that VR is solely an entertainment medium. Through examination of Lean Principles and Video Game Development immersion strategies this research highlights the little recognized area of an Immersive Manufacturing Training and Design Testing Application. It is clear that Modern manufacturing environments need to become aware of Lean philosophies of adaptability. There is a requirement to inform companies about utilisation of the latest technologies in order to educate workforces in an efficient and Lean manner. The software runs a simulation on a Zspace 3D display screen in a 3D VR format.",
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"content": "This paper debates the necessity of implementing Virtual Reality Technology as a training tool within Lean Manufacturing Environments (LME). The topic for discussion surrounding this area is the need for a user friendly package that utilizes game and advanced Virtual Reality (VR) Technology to encompass the principles of the Lean approach to manufacturing. Fundamental principles adopted by video game developers attempting to immerse the user could provide a key, through allowing for a fully immersive manufacturing simulation software package. The implementation of VR and training software that would not only teach, but also showcase new technology and show its relevance in a manufacturing system. As a result the use of Lean philosophy acts as a conduit in the implementation of the VR software in adaptable modern manufacturing. Literature within Lean Manufacturing and Video Game Development Immersion Methodologies allow for a juxtaposition between the two, through promoting the validity of novel simulation training techniques. Evaluating case studies of Lean Manufacturing applications will ascertain the need for innovative adaptations, by determining whether solutions could be further improved by latest technological advancements. This paper critically appraises gaming technology and its evolution towards sophisticated design solutions. Learning theories adopted through gaming reveal new approaches to motivational drivers in developing necessary skill sets for modern workforces. Studies surrounding objective based instructional learning highlight rarely acknowledged fields in manufacturing simulation testing. Project Sponsor: Nottingham Trent University & PepsiCo The simulation software is to be built using Unity3D with scripting in C# and Java Script which emulates running of a manufacturing cell within a Lean environment. Its purpose is to train and educate personnel through simulating a functioning manufacturing cell. The software displays potential Lean wastes and problems such as bottle necking. It is imperative to the development of modern manufacturing environments that new simulation techniques in educating workforces, creating prototypes and testing are embraced. Currently only the latter two developments are predominantly created in unison. In Lean, this is wasteful in terms of transport and skill if these are not performed in-house. The need for a more user friendly and intuitive simulation experience requires clarity for potential manufacturers in order to adopt this methodology. Not enough varied Lean manufacturing companies embody Lean principles on a computational software level and as a result could potentially leave entire generations without modern manufacturing skill sets. The concept of VR used in modern Manufacturing Simulation Software (MSS) can be utilised to dispel any belief that VR is solely an entertainment medium. Through examination of Lean Principles and Video Game Development immersion strategies this research highlights the little recognized area of an Immersive Manufacturing Training and Design Testing Application. It is clear that Modern manufacturing environments need to become aware of Lean philosophies of adaptability. There is a requirement to inform companies about utilisation of the latest technologies in order to educate workforces in an efficient and Lean manner. The software runs a simulation on a Zspace 3D display screen in a 3D VR format.",
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"abstract": "This study presents an empirical evidence of benefit of narrative video clips in embedded virtual reality (VR) websites of hotels for relieving travel security concern. Even though it was proven that VR functions do provide some relief in travel security concern, a stronger VR website can be built when narrative video clips that show video clips with narration about important aspects of the hotel. Thus we created a video clip that showed and narrated about the escape route from the hotel room, another video clip that showed and narrated about surrounding neighborhood. We then conducted experiments with this enhanced VR website of a hotel by having human subjects play with the website and fill out a questionnaire. The result confirms our hypothesis that there is a statistically significant relationship between the degree of travel security concern and psychological relief caused by the use of embedded VR functions with narrative video clips of a hotel website.",
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"doi": "10.1109/TransAI51903.2021.00011",
"title": "An Immersive Model of User Trust in Conversational Agents in Virtual Reality",
"normalizedTitle": "An Immersive Model of User Trust in Conversational Agents in Virtual Reality",
"abstract": "Conversational agents (CAs) have been widely adopted for various purposes, ranging from personal assistants to health information providers. While the research on CAs is growing rapidly, less attention is paid to CAs in virtual reality (VR) environments with respect to how the design of these agents influences their trustworthiness as perceived by users, which is key to the adoption and use of VR products featuring CAs. Accordingly, this position paper conceptualizes an immersive model of user trust in CAs in VR. The model is centered around users’ sense of co-presence with CAs in VR, which is influenced by the agents’ embodiment, expressiveness, and responsiveness.",
"abstracts": [
{
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"content": "Conversational agents (CAs) have been widely adopted for various purposes, ranging from personal assistants to health information providers. While the research on CAs is growing rapidly, less attention is paid to CAs in virtual reality (VR) environments with respect to how the design of these agents influences their trustworthiness as perceived by users, which is key to the adoption and use of VR products featuring CAs. Accordingly, this position paper conceptualizes an immersive model of user trust in CAs in VR. The model is centered around users’ sense of co-presence with CAs in VR, which is influenced by the agents’ embodiment, expressiveness, and responsiveness.",
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"normalizedAbstract": "Conversational agents (CAs) have been widely adopted for various purposes, ranging from personal assistants to health information providers. While the research on CAs is growing rapidly, less attention is paid to CAs in virtual reality (VR) environments with respect to how the design of these agents influences their trustworthiness as perceived by users, which is key to the adoption and use of VR products featuring CAs. Accordingly, this position paper conceptualizes an immersive model of user trust in CAs in VR. The model is centered around users’ sense of co-presence with CAs in VR, which is influenced by the agents’ embodiment, expressiveness, and responsiveness.",
"fno": "341200a017",
"keywords": [
"Chatbots",
"Medical Information Systems",
"Virtual Reality",
"C As",
"Virtual Reality Environments",
"VR Products",
"Immersive Model",
"User Trust",
"Conversational Agents",
"Health Information Providers",
"Agent Embodiment",
"Solid Modeling",
"Virtual Reality",
"Distance Measurement",
"Artificial Intelligence",
"Conversational Agents Trust Virtual Reality Virtual Conversational Agents"
],
"authors": [
{
"affiliation": "Northeastern University,Khoury College of Computer Sciences,Boston,MA",
"fullName": "Caglar Yildirim",
"givenName": "Caglar",
"surname": "Yildirim",
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"pages": "17-18",
"year": "2021",
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