In-person tele-presence through hybrid camera networks

本项目旨在开发新的理论和算法，用于基于混合摄像机网络实时捕获运动物体的精确密集3D模型。后者由静态外部红、绿、蓝加深度（RGB-D）摄像头和动态头戴式普通摄像头组成。科学上的新奇之处将是密集的、非刚性的、协作的运动结构理论，这些理论可以最大限度地利用这种混合信息，例如利用精确的头姿信息。其结果是一个可以制作现场全身动画的工作原型，从而利用了信息技术行业的新应用。具有高度战略意义的例子包括三维远程呈现、增强远程操作、机器人和智能运输系统。

This project aims to develop novel theories and algorithms for live capturing of accurate dense 3D models of moving subjects based on hybrid camera networks. The latter consist of a mix of static external red, green, blue plus depth (RGB-D) cameras and a dynamic head-mounted regular camera. The scientific novelties will be dense, non-rigid, and collaborative structure-from-motion theories that maximise the exploitation of such hybrid information, for instance by utilising exact head-pose information. The outcome is a working prototype producing live full-body animations, thus leveraging new applications in the Information Technology industry. Highly strategically relevant examples are given by 3D tele-presence, enhanced tele-operation, robotics, and intelligent transportation systems.