PMD-Modeling, -Simulation, -Evaluation & Algorithmics

距离传感飞行时间（ToF）相机的发展已经有15年的历史了。光子混合装置（PMD）是最早由德国锡根大学的Rudolf Schwarte教授提出并原型实现的方法之一。PMD概念是PMD技术有限公司的基础核心，PMD技术有限公司是世界领先的ToF相机生产商之一，拥有约65名员工。所要求的知识转移项目的核心思想是基于计算机图形学和工业合作伙伴pmd技术有限公司各自的发展状况，对ToF相机的传感器建模、仿真、评估和算法等主题进行综合研究和概念集成。这种方法将促进在过去十年中提出的相关研究成果的进步，以便将其集成到实际应用的商业产品中。此外，我们将开发新的解决方案，以ToF相机系统的扰动效应，这是迄今为止很少研究的。在这个项目中，我们将在之前和当前DFG资助的研究项目的基础上，研究非常当前和实际的问题，同时这些问题具有很强的科学兴趣。这包括对传感器建模、仿真和评估的综合研究，从而可以对未来的传感器和算法进行定量评估，从芯片级到驱动器级特定测量误差的校正。此外，在算法背景下，我们将研究运动伪影和多路径问题等相关问题。寻找强大而高效的解决方案来解决这些问题将极大地提高数据质量，从而为ToF相机开辟新的应用领域。

Range sensing Time-of-Flight (ToF) cameras have been actively developed for some 15 years now. The Photonic Mixing Devices (PMD) is one of the first approaches that was introduced and prototypically realized by Prof. Dr. Rudolf Schwarte from the University of Siegen. The PMD concept was the nucleus for the foundation of the pmd technologies gmbh, which is one of the world leading ToF camera producers, with a staff of about 65 employees.The central idea of the requested knowledge transfer project is the integrated investigation and conceptual integration of the topics sensor modeling, simulation, evaluation and algorithmics of ToF cameras based on the respective development status at the chair for Computer Graphics and the industrial partner pmd technologies gmbh. This approach will promote the advancement of relevant research results, presented in the last decade, towards integration into commercial products for real-world applications. Furthermore, we will develop new solution to perturbing effects of ToF camera systems, which have been little investigated until now.In this project we will, on the basis of prior and current DFG funded research projects, investigate very current and practical questions, which are, at the same time, of strong scientific interest. This involves an integrated investigation of sensor modeling, simulation and evaluation, which allows for quantitative assessment of future sensors and algorithms, from the chip level up to the correction of specific measurement errors at driver level. Furthermore, in the algorithmic context, we will research relevant questions such as motion artefacts and multi-path problems. Finding robust and efficient solutions to resolve these problems will strongly improve the data quality, and thus open up new application domains for ToF cameras.