Real-Time Modeling and Registration of Dynamic Geometry

增强现实市场预计到2020年将达到1200亿美元。消费级增强现实设备（例如微软HoloLens）的出现受到能够同时捕获颜色和深度的实时传感器（例如微软Kinect）的技术飞跃的推动。虽然这些传感器提供了一种测量真实的世界的3D几何形状的方法，但实时处理几何形状特别具有挑战性。例如，许多技术只关注特定的子问题，如面部、身体或手部跟踪，因此通常假设相机观察到的对象具有已知的几何形状。使这些算法适应未知的、动态的和不断变化的环境是一个根本性的挑战，特别是当针对实时应用时，它们的效率和功耗要求相互冲突。

The augmented reality market is forecast to reach $120 billion by 2020. The advent of consumer-level augmented reality devices (e.g. Microsoft HoloLens) has been fuelled by technological leaps in real-time sensors capable of simultaneously capturing colour and depth (e.g. Microsoft Kinect). While these sensors provide a way of measuring the 3D geometry of the real world, processing geometry in real-time is particularly challenging. For example, many techniques only focus on specific sub-problems like face, body or hand tracking, and thus often assume the object being observed by the camera is of known geometry. Adapting these algorithms to cope with an unknown, dynamic and ever-changing environment is a fundamental challenge, especially when targeting real-time applications with their conflicting requirements of efficiency and power consumption.