Online CAD reconstruction with hand-held depth cameras (HandCAD-2)

三维几何计算机模型（CAD模型）用于许多技术应用，例如建筑、制造、仿真和计算机游戏。这些模型服务于非常不同的目的，但有一个共同点，即它们代表了对真实的世界中刚体的模仿。CAD模型可以由设计师在几个复杂的步骤中手动创建，也可以在计算机上进行创造性过程。或者，传感器捕获现有对象或现有环境，然后根据测量结果自动生成几何模型（CAD重建）。如今，低成本的深度相机可用于CAD重建。除了这样收集的几何数据之外，还需要检测到的对象的附加抽象信息，例如它们的属性、对称性或特征。此外，CAD重建应该是快速和容易执行，即使没有专家knowledge.In本研究项目的方法，从手持相机的深度传感器数据的CAD模型的自动生成的开发和研究。在这里，在线计算重建的单个对象和完整的内部或外部场景的抽象模型的形式被认为具有不同的分辨率水平。重建应使用低性能计算硬件生成，以便可以在采集期间显示结果。具体的挑战是非平面、无结构或对称的表面和动态对象，例如在场景中移动的人。从长远来看，希望对重建的对象得出额外的结论，例如：它是哪个对象？物体是固定的还是可移动的？物体（例如门）可能的运动是什么？

Three-dimensional geometric computer models (CAD models) are used in many technical applications, such as in construction, manufacturing, simulation and in computer games. These models serve very different purposes, but have in common that they represent an imitation of rigid bodies in the real world. A CAD model is created either manually in several complex steps of a designer, or in a creative process on the computer. Alternatively, an existing object or an existing environment is captured by sensors and then a geometric model is automatically generated from the measurements (CAD reconstruction). Today, low-cost depth cameras are available for CAD reconstruction. In addition to the geometric data thus collected, additional abstract information of the detected objects, such as their properties, symmetries or features are desirable. Furthermore, the CAD reconstruction should be quick and easy to perform even without expert knowledge.In this research project methods for the automatic generation of CAD models from sensor data from hand-held cameras depth are developed and investigated. Here, the online computable reconstruction of individual objects and of complete interior or exterior scenes in the form of abstract models is considered with different resolution levels. The reconstruction should be generated with low performance computing hardware, such that the results can be displayed already during the acquisition. Specific challenges are non-planar, structure-less or symmetric surfaces and dynamic objects, such as people moving through the scene. In the long run, it would be desirable to draw additional conclusions on the reconstructed objects, such as: Which object is it? Is the object fixed or movable? What are the possible movements of the object (e.g. a door)?