Yanran Dai, Jing Li, Yuqi Jiang, Haidong Qin, Bang Liang, Shikuan Hong, Haozhe Pan, Tao Yang
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引用次数: 0
摘要
自由视角视频允许用户从任何虚拟视角观看物体,创造身临其境的视觉体验。这项技术增强了多媒体表演的互动性和自由度。然而,许多自由视点视频合成方法很难满足高精度实时工作的要求,尤其是对于面积大、移动物体多的运动场地。为了解决这些问题,我们提出了一种基于距离场加速的自由视点视频合成方法。其核心思想是融合多视角距离场信息,并利用这些信息自适应地调整搜索步长。自适应步长搜索有两种用途:快速估计多物体三维表面和基于全局遮挡判断的合成视图渲染。我们利用 CUDA 和 OpenGL 框架,通过并行计算实现了我们的想法,并使用真实世界和模拟实验数据集进行评估。结果表明,所提出的方法可以在大型运动场上以 25 fps 的速度渲染包含多个物体的自由视点视频。此外,我们合成的新视角图像的视觉质量超过了最先进的基于神经渲染的方法。
Real-time distance field acceleration based free-viewpoint video synthesis for large sports fields
Free-viewpoint video allows the user to view objects from any virtual perspective, creating an immersive visual experience. This technology enhances the interactivity and freedom of multimedia performances. However, many free-viewpoint video synthesis methods hardly satisfy the requirement to work in real time with high precision, particularly for sports fields having large areas and numerous moving objects. To address these issues, we propose a free-viewpoint video synthesis method based on distance field acceleration. The central idea is to fuse multi-view distance field information and use it to adjust the search step size adaptively. Adaptive step size search is used in two ways: for fast estimation of multi-object three-dimensional surfaces, and synthetic view rendering based on global occlusion judgement. We have implemented our ideas using parallel computing for interactive display, using CUDA and OpenGL frameworks, and have used real-world and simulated experimental datasets for evaluation. The results show that the proposed method can render free-viewpoint videos with multiple objects on large sports fields at 25 fps. Furthermore, the visual quality of our synthetic novel viewpoint images exceeds that of state-of-the-art neural-rendering-based methods.
期刊介绍:
Computational Visual Media is a peer-reviewed open access journal. It publishes original high-quality research papers and significant review articles on novel ideas, methods, and systems relevant to visual media.
Computational Visual Media publishes articles that focus on, but are not limited to, the following areas:
• Editing and composition of visual media
• Geometric computing for images and video
• Geometry modeling and processing
• Machine learning for visual media
• Physically based animation
• Realistic rendering
• Recognition and understanding of visual media
• Visual computing for robotics
• Visualization and visual analytics
Other interdisciplinary research into visual media that combines aspects of computer graphics, computer vision, image and video processing, geometric computing, and machine learning is also within the journal''s scope.
This is an open access journal, published quarterly by Tsinghua University Press and Springer. The open access fees (article-processing charges) are fully sponsored by Tsinghua University, China. Authors can publish in the journal without any additional charges.