Computational Photography for Capturing Virtual Environments

用于捕捉虚拟环境的计算摄影

• 批准号: 311873-2013
• 负责人: Lang, Jochen
• 金额: $ 1.09万
• 依托单位: University of Ottawa
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=571639
• 关键词: Computational; Photography; Capturing; Virtual; Environments

Image-based virtual environments for navigation, training and computer animation are attractive, but generating high-quality and physically plausible large environments is still beyond today's technology. Many research challenges remain, including making large image-based environments consistent despite changes in illumination during capture and displaying them afterwards under different illumination. Another major challenge is to give image-based environments some interactive physical behaviour, e.g., a response to interactive forces. Image-based virtual environments must become richer to provide these new capabilities which will enable novel applications in the computer animation industry, in mobile navigation and in security, in monitoring of assets and in simulation-based training. The proposed research addresses these challenges by changing the capture process to include computation directly into the image acquisition. Computation during capture can steer the imaging process to acquire the necessary information for the image-based environment, e.g., through on-line tracking of surfaces or by adjusting image exposure to capture all image areas correctly exposed. Scalability of the capture process will be addressed by investigating incremental methods which allow to add new images to an existing environment. Incremental methods will also help with dynamic scenarios where the environment evolves over time. The research will have excellent opportunities to train highly-qualified personnel in fields with many Canadian small and medium enterprises ready to take-up this personnel. Software engineering skills are critically important in today's economy and this research will create software experts in real-world sensors and cameras, in computer vision and in mobile parallel computing on today's graphics processing units (GPU) and on the CPU, as well as in human computer interaction but it will also ensure that highly-qualified personnel will acquire the fundamental mathematical and physical background to set them apart and ensure their long-term success.

用于导航、训练和计算机动画的基于图像的虚拟环境是有吸引力的，但是生成高质量和物理上合理的大环境仍然超出了今天的技术。许多研究挑战仍然存在，包括使大型基于图像的环境保持一致，尽管在捕获期间照明发生变化，并在不同照明下显示它们。另一个主要挑战是赋予基于图像的环境一些交互式物理行为，例如，对相互作用力的反应。基于图像的虚拟环境必须变得更丰富，以提供这些新的功能，这将使新的应用程序在计算机动画行业，在移动的导航和安全，在资产监控和基于模拟的培训。 拟议的研究通过改变捕获过程来解决这些挑战，将计算直接纳入图像采集。捕获期间的计算可以引导成像过程以获取基于图像的环境的必要信息，例如，通过表面的在线跟踪或通过调整图像曝光来捕获正确曝光的所有图像区域。捕获过程的可扩展性将通过研究允许向现有环境添加新图像的增量方法来解决。增量方法还有助于处理环境随时间演变的动态场景。这项研究将有很好的机会，培养高素质的人才领域与许多加拿大中小型企业准备采取这些人员。软件工程技能在当今的经济中至关重要，这项研究将在现实世界的传感器和相机，计算机视觉和移动的并行计算中培养软件专家，这些软件专家都是在当今的图形处理单元（GPU）和CPU上进行的。以及人机交互，但它也将确保高度-合格的人员将获得基本的数学和物理背景，使他们脱颖而出，并确保他们的长期成功。