IMAP: Image-based modeling with autonomous positioning

在过去的20年里，光学三维物体数字化系统有了显著的发展。目前，以亚毫米级精度和分辨率对各种物体的形状进行数字化是可能的。这种基于视觉的技术对工业检验、原型设计、设计和艺术、定制论文、考古文献以及更普遍的模拟等各个领域做出了重大贡献。加拿大在这一领域处于世界领先地位，在过去的10年里，一些服务提供商和设备制造商蓬勃发展。目前，设计人员面临的主要挑战是提高数字化系统的灵活性和实现更好的表面外观捕获质量。这些挑战提出了计算机视觉领域的基本问题。首先，开发一个基于图像内容的智能自动引用系统，应该同时处理数百甚至数千张必须相互引用的图像的捕获和集成。该系统应提供基于自然和人工目标基准的定位质量诊断。这种自定位系统除了作为表面外观捕获工具外，还将用于促进几何形状的恢复。与从一组有限的图像中捕获纹理不同，它有望实现对光场和物体反射率特性的交互捕获，从而获得当前纹理捕获和映射方法无法比拟的质量。该项目将培养4名博士研究生和少量本科生。该项目由一家专门从事3D数字化的公司以及加拿大国防研究与发展公司的移动机器人研究团队提供支持。

Over the last 20 years, optical 3D object digitizing systems have evolved significantly. It is currently possible to digitize the shape of a wide range of objects with sub-millimetre accuracy and resolution. This type of vision-based technology has significantly contributed to various fields such as industrial inspection, prototyping, design and arts, tailor-made ortheses, archaeology documentation and, more generally, to simulation. Canada is among the world leaders in this field and several service providers and equipment manufacturers have blossomed in the last 10 years. Currently, the predominant challenges faced by designers consist in improving the flexibility of the digitizing systems and achieving better quality in capturing surface appearance. These challenges raise fundamental problems in the field of computer vision. First, developing an intelligent auto-referencing system based on image content should deal concurrently with capturing and integrating hundreds, and even thousands of images that must be referenced to each other. The system should provide a diagnosis of the positioning quality based on natural and artificial target fiducials. This self-positioning system will then be exploited for facilitating geometry recovery in addition to serving as a tool for surface appearance capture. Instead of capturing the texture from a limited set of images, it is expected to make interactive capture of light fields and reflectance properties of objects possible for obtaining incomparable quality with respect to current texture capture and mapping methods. This project will contribute to the training of 4 students at the doctorate level and a few undergraduate students. The project is supported by a company specialized in 3D digitizing as well as a research team in mobile robotics at Defence Research and Development Canada.