IMAP: Image-based modeling with autonomous positioning

在过去的20年里，光学3D物体数字化系统已经有了显著的发展。目前可以以亚毫米的精度和分辨率对各种物体的形状进行测量。这种基于视觉的技术在工业检测、原型制作、设计和艺术、定制矫形器、考古学文献以及更普遍的模拟等各个领域都做出了重大贡献。加拿大是这一领域的世界领导者之一，在过去10年中，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在于提高数字化系统的灵活性，并在捕获表面外观时实现更好的质量。这些挑战提出了计算机视觉领域的基本问题。首先，开发基于图像内容的智能自动参考系统应该同时处理捕获和集成数百甚至数千个必须相互参考的图像。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，然后将被利用，以促进几何恢复，除了作为一个工具，表面外观捕捉。代替从有限的图像集合捕获纹理，期望使对象的光场和反射特性的交互式捕获成为可能，以获得相对于当前纹理捕获和映射方法的无与伦比的质量。该项目将有助于培养4名博士生和一些本科生。该项目得到了一家专门从事3D数字化的公司以及加拿大国防研究与发展部移动的机器人研究团队的支持。

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.