In this paper, we propose a new geometric model that includes a fourth-order partial differential equation (PDE) for reconstructing 2D curves. For instance, we use this model to reproduce letters in Time Roman font. T...
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In this paper, we propose a new geometric model that includes a fourth-order partial differential equation (PDE) for reconstructing 2D curves. For instance, we use this model to reproduce letters in Time Roman font. The method of fundamental solutions (MFS), which is a simple and easily implemented meshless method, is employed for solving the proposed PDEs. In addition, no fictitious boundary is required for the proposed MFS formulation, which further simplifies the implementation of the numerical method. Three examples of 2D curve reproduction are presented to demonstrate the effectiveness of the proposed model.
We present a novel graph-based simulation approach for generating micro wrinkle geometry on human skin, which can easily scale up to the micro-meter range and millions of wrinkles. The simulation first samples pores o...
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We present a novel graph-based simulation approach for generating micro wrinkle geometry on human skin, which can easily scale up to the micro-meter range and millions of wrinkles. The simulation first samples pores on the skin and treats them as nodes in a graph. These nodes are then connected and the resulting edges become candidate wrinkles. An iterative optimization inspired by pedestrian trail formation is then used to assign weights to those edges, i.e., to carve out the wrinkles. Finally, we convert the graph to a detailed skin displacement map using novel shape functions implemented in graphics shaders. Our simulation and displacement map creation steps expose fine controls over the appearance at real-time framerates suitable for interactive exploration and design. We demonstrate the effectiveness of the generated wrinkles by enhancing state-of-art 3D reconstructions of real human subjects with simulated micro wrinkles, and furthermore propose an artist-driven design flow for adding micro wrinkles to fictional characters.
Movies, advertisements, and promotional videos are Intellectual Property (IP) and are often shared on open access medium as part of the business. Fueled by the advancements in tech-nology, piracy has become more rampa...
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We introduce a simplification method based on irregular triangular networks to create a generalized digital elevation model (DEM) for land surface segmentation. The quadric error metrics simplification (QEMS) algorith...
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We introduce a simplification method based on irregular triangular networks to create a generalized digital elevation model (DEM) for land surface segmentation. The quadric error metrics simplification (QEMS) algorithm was used to generalize the DEM as a method that follows the theory of optimal triangle for (land) surface representation. Its use for land surface modeling is novel, however, it is well known in computer graphics. Comparison of QEMS with the maximum z-tolerance method shows priority in terms of root mean square error. Numerical expression of the value concentration of the third-order variables (curvature changes) around zero (K-0) was used as an indicator of elementary form representation in generalized DEMs. K-0 was calculated for a set of DEMs at several generalization levels in two different territories, as well as for comparably generalized artificial surfaces. K-0 values of real DEMs vary significantly with generalization levels and character of the landforms, and their maxima point to the generalization levels that best preserve the information about elementary forms of various hierarchical levels. Differences between K-0 of real DEMs and artificial surfaces confirm the same.
Sphere tracing is a common raytracing technique used for rendering implicit surfaces defined by a signed distance function (SDF). However, these distance functions are often expensive to compute, prohibiting several r...
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Sphere tracing is a common raytracing technique used for rendering implicit surfaces defined by a signed distance function (SDF). However, these distance functions are often expensive to compute, prohibiting several real-time applications despite recent efforts to accelerate them. This paper presents quadric tracing, a method to precompute an augmented distance field that significantly accelerates rendering. This novel method supports two configurations: (i) accelerating raytracing without losing precision, so the original SDF is still needed;(ii) entirely replacing the SDF and tracing an interpolated surface. Quadric tracing can offer 20% to 100% speedup in rendering static scenes and thereby amortizes the slowdown caused by the complexity of the geometry.
Some of these so-called AIoT applications include intelligent image processing in smart factories to monitor machinery conditions and control raw material inventory, identifying abnormalities in medical images, and au...
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Some of these so-called AIoT applications include intelligent image processing in smart factories to monitor machinery conditions and control raw material inventory, identifying abnormalities in medical images, and automatic real-time scanning and recognition of license plates in traffic to locate stolen cars.
The topics covered in this special issue include (i) intelligent image processing applications and services to fulfill the real-time processing and performance demands, (ii) real-time deep learning and machine learning solutions to improve computational speed and increase recognition rates at network edges, (iii) new frameworks to optimize real-time AIoT image processing, and (iv) combining intelligent real-time image processing with edge computing, fog computing, and relevant techniques to balance the computational workloads between IoT devices and the server side.
Fan and Guan [1] have developed a deep face verification framework based on SIFT (scale invariant feature transform) and CNN (convolutional neural network) methods.
The increase in marine litter is slowly becoming a significant problem, for which various recognition techniques have been proposed and are still being. Artificial Intelligence (AI) based methodologies have emerged as...
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This special section of the IEEE Transactions on Visualization and computer graphics (IEEE TVCG) presents the five most highly rated papers from the 2021 IEEE Pacific Visualization Symposium (IEEE PacificVis). This ye...
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This special section of the IEEE Transactions on Visualization and computer graphics (IEEE TVCG) presents the five most highly rated papers from the 2021 IEEE Pacific Visualization Symposium (IEEE PacificVis). This year, IEEE PacificVis was scheduled to be hosted by Tianjin University and held in Tianjin, China, from April 19 to 22, 2021. IEEE PacificVis, sponsored by the IEEE Visualization and graphics Technical Committee (VGTC), aims to foster greater exchange between visualization researchers and practitioners, especially in the Asia-Pacific region. This forum has grown to be a truly international event, attracting submissions and attendees from many countries in the Asia-Pacific and Europe, America, and beyond. Thus, IEEE PacificVis is serving the additional purposes of sharing the latest advances in visualization with researchers and practitioners in the region and introducing research developments in the region to the broader international visualization research community.
An overview of the use of Generative Adversarial Networks (GANs) in computer vision—image synthesis and manipulation—is given in this study. A generator and a discriminator are two complex neural networks that are t...
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ISBN:
(数字)9798331530389
ISBN:
(纸本)9798331530396
An overview of the use of Generative Adversarial Networks (GANs) in computer vision—image synthesis and manipulation—is given in this study. A generator and a discriminator are two complex neural networks that are trained in competition to form GANs. Owing to the formidable capabilities of deep neural networks and their adversarial training approach, GANs exhibit the ability to generate realistic and plausible images, thereby demonstrating remarkable prowess across various applications in the realm of image synthesis and manipulation. This survey paper delves into recent GAN-related research. Working on the progressive GANs model technique, the authors find out how capable it is compared to other GANs algorithms. Building an image synthesis Progressive Generative Adversarial Networks (ProGANs) is a complex process with several steps that work together to produce high-quality pictures.
This work deals with procedural content generation, specializing in content generation in the fields of computer graphics and computer games. Even more precisely, it deals with the procedural generation of three-dimen...
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ISBN:
(数字)9798350379365
ISBN:
(纸本)9798350379372
This work deals with procedural content generation, specializing in content generation in the fields of computer graphics and computer games. Even more precisely, it deals with the procedural generation of three-dimensional polygonal surface models of rivers. In the introductory part, the paper provides an overview of related procedural content generation principles using noise generating functions and more complex simulation techniques. Then, it presents a within this work designed algorithm for the procedural generation of a river model by creating its bed using the designed concept of control tiles, which allow controlling the direction and shape of the river. The generator's goal is to provide a tool for creating river models that can be integrated into the environment of 3D computer games.
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