With the continuous improvement of China's social and economic level, people's aesthetic ability is also constantly improving. At present, the full application of computer graphics and illustration art in the ...
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In this article, a survey of the point cloud compression (PCC) methods by organizing them with respect to the data structure, coding representation space, and prediction strategies is presented. Two paramount families...
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In this article, a survey of the point cloud compression (PCC) methods by organizing them with respect to the data structure, coding representation space, and prediction strategies is presented. Two paramount families of approaches reported in the literature-the projection- and octree-based methods-are proven to be efficient for encoding dense and sparse point clouds, respectively. These approaches are the pillars on which the Moving Picture Experts Group Committee developed two PCC standards published as final international standards in 2020 and early 2021, respectively, under the names: video-based PCC and geometry-based PCC. After surveying the current approaches for PCC, the technologies underlying the two standards are described in detail from an encoder perspective, providing guidance for potential standard implementors. In addition, experiment evaluations in terms of compression performances for both solutions are provided.
In this study, we evaluated the codec agnostic approach of video-based point cloud compression (V-PCC) by applying several video codecs to V-PCC. The main concept of V-PCC is to use a video codec to compress the 2D pa...
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In this study, we evaluated the codec agnostic approach of video-based point cloud compression (V-PCC) by applying several video codecs to V-PCC. The main concept of V-PCC is to use a video codec to compress the 2D patch images generated from a 3D point cloud. As a new immersive media standard of the Moving Picture Experts Group (MPEG), V-PCC is designed to support the codec agnostic approach, which can be employed to compress point cloud data using any video codec. The V-PCC reference software is currently designed using MPEG High-Efficiency Video Coding. We extended the evaluation of video codec applicability for PCC using well-known MPEG video coding standards, such as Advanced Video Coding, Essential Video Coding, and Versatile Video Coding. We identified several key strategies for applying a video codec to V-PCC to maximize the compression efficiency or computational complexity during the evaluation. Furthermore, the coding efficiency and time complexity of each codec are tested. The evaluation tests revealed that V-PCC supports the codec agnostic approach, and that the performance of the video codec is positively correlated with the V-PCC final coding efficiency. Reviewing these key strategies would help to develop V-PCC with different video codecs based on their profiles and levels.
Virtual cinematography is a fundamental problem spanning a wide range of computer graphics applications. Software for animation, videogames, scientific visualization, and other applications frequently require computat...
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Virtual cinematography is a fundamental problem spanning a wide range of computer graphics applications. Software for animation, videogames, scientific visualization, and other applications frequently require computational tools capable of automatically determining how to control a camera to capture an image with desired properties. In this thesis, we propose an expressive, controllable, and efficient methodology to virtual cinematography automation that is compatible with both online and offline applications. By identifying the minima of an unconstrained, continuous objective function matching some desired compositional behaviors, such as those common in live action photography or cinematography, a suitable camera pose or path can be automatically determined using standard search algorithms. With several constraints on function form, multiple objective functions can be combined into a single optimizable function in several ways, which can be further extended to model the smoothness of the discovered camera path with a deformable spline based on an active contour model. These abstract mathematical techniques are supported by a novel domain-specific programming language, complete with a suite of program analysis and transformation tools capable of automatic differentiation, value range analysis, and program optimization for programs representing run-time specified objective functions, all of which is modularly integrated with Unreal Engine 4 for rendering and user input. To make this system usable by mathematical non-experts, we explore two ***, we provide a library of predefined objective functions corresponding to standard photographic and cinematographic compositional rules, complete with recipes for how to combine them to achieve common ***, we use NLP-derived machine learning techniques on a novel dataset containing annotations on ~1M frames from 60 feature films, to attempt to automatically learn objective functions corresponding to
With the development of motion capture technologies, 3D action recognition has become a popular task that finds great applicability in many areas, such as augmented reality, human-computer interaction, sports, or heal...
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With the development of motion capture technologies, 3D action recognition has become a popular task that finds great applicability in many areas, such as augmented reality, human-computer interaction, sports, or healthcare. On the other hand, the acquisition of 3D human skeleton data is an expensive and time-consuming process, mainly due to the high costs of capturing technologies and the absence of suitable actors. We overcome these issues by focusing on the 2D skeleton modality that can be easily extracted from ordinary videos. The objective of this work is to demonstrate a high descriptive power of such a 2D skeleton modality by achieving accuracy on the task of daily action recognition competitive to 3D skeleton data. More importantly, we thoroughly analyze the factors that significantly influence the 2D recognition accuracy, such as the sensitivity towards data normalization, scaling, quantization, and 3D-to-2D distortions in skeleton orientations and sizes, which are caused by the loss of depth dimension and fixed-angle camera view. We also provide valuable insights on how to mitigate these problems to increase recognition accuracy significantly. The experimental evaluation is conducted on three datasets different in nature. The ability to learn different types of actions better using either 2D or 3D skeletons is also reported. Throughout experiments, a generic light-weight LSTM network is used, whose architecture can be easily tuned to achieve the desired trade-off between its accuracy and efficiency. We show that the proposed approach achieves not only the state-of-the-art results in 2D skeleton action recognition but is also highly competitive to the best-performing methods classifying 3D skeleton sequences or the visual content extracted from ordinary videos.
IEEE computer graphics and Applications (IEEE CG&A) has long stood at the intersection of innovation and application in the computer graphics community. To acknowledge the individuals and teams who elevate this mi...
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IEEE computer graphics and Applications (IEEE CG&A) has long stood at the intersection of innovation and application in the computer graphics community. To acknowledge the individuals and teams who elevate this mission, IEEE CG&A offers a suite of prestigious awards recognizing exceptional contributions in research, editorial leadership, and community service. This article presents a comprehensive overview of the IEEE CG&A awards program, highlighting the criteria, selection processes, and intent of five key honors: the Best Paper Award, the Test of Time Award, the Outstanding Associate Editor Award, the Outstanding Department Editor Award, and the Outstanding Guest Editor Award. In addition to detailing these accolades, we explore the broader impact of these recognitions through real-world examples—such as Brown University's celebration of its faculty recipients—demonstrating how IEEE CG&A honors not only individual achievement, but also fosters institutional pride, mentorship, and enduring influence in the field.
With the advent of the image age, the popularity of war-themed film and television dramas in the new century has promoted a new wave of thematic narratives. Facing the era of computer graphics, the main theme narrativ...
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Simulation of atomic force microscopy (AFM) computationally emulates experimental scanning of a biomolecular structure to produce topographic images that can be correlated with measured images. Its application to the ...
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Simulation of atomic force microscopy (AFM) computationally emulates experimental scanning of a biomolecular structure to produce topographic images that can be correlated with measured images. Its application to the enormous amount of available high-resolution structures, as well as to molecular dynamics modelling data, facilitates the quantitative interpretation of experimental observations by inferring atomistic information from resolution-limited measured topographies. The computation required to generate a simulated AFM image generally includes the calculation of contacts between the scanning tip and all atoms from the biomolecular structure. However, since only contacts with surface atoms are relevant, a filtering method shall highly improve the efficiency of simulated AFM computations. In this report, we address this issue and present an elegant solution based on graphics processing unit (GPU) computations that significantly accelerates the computation of simulated AFM images. This method not only allows for the visualization of biomolecular structures combined with ultra-fast synchronized calculation and graphical representation of corresponding simulated AFM images (live simulation AFM), but, as we demonstrate, it can also reduce the computational effort during the automatized fitting of atomistic structures into measured AFM topographies by orders of magnitude. Hence, the developed method will play an important role in post-experimental computational analysis involving simulated AFM, including expected applications in machine learning approaches. The implementation is realized in our BioAFMviewer software (ver. 3) package for simulated AFM of biomolecular structures and dynamics.
computer image came into being at the end of 1980s, and it has experienced more than 30 years of development. Image processing technology has been widely used and has become modern applied science. computer technology...
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We all know that there is an exponential growth in the production of digital data. The user of the internet approaches the cloud service providers to upload the video data into the cloud. The cost and size of the digi...
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