Quality-driven autonomous 3D reconstruction of large-scale scenes

在过去的30年里，显示器和电视一直是占主导地位的显示设备。它们只能显示2D内容，而使用当今的数码相机可以很容易地获取2D内容。随着虚拟现实（VR）设备的实用性和普及，用户可以从选定的视点和方向观看3D内容，因此，如何高效、经济地捕捉3D物体和场景是一个重要的问题。******获取小物体三维形状的技术已经成熟。用户可以使用距离扫描仪从不同的侧面扫描给定的物体，然后将3D点云注册在一起，生成一个表面模型。在这方面，我和我的合作者开发了一种最先进的算法，通过使用机械臂将扫描仪定位在战略选择的位置，使扫描过程自动化。然而，如何自主获取大型户外场景的高质量模型仍然是一个有待解决的问题。******大型场地的3D重建在城市规划、地质考古调查、虚拟旅游、军事模拟等领域有着广泛的应用。它是许多研究领域的一个活跃话题，包括计算机视觉、图形学、机器人、土木工程和遥感。在过去，人们经常求助于载人机载激光雷达系统，其成本令人生畏。由于无人驾驶飞行器（uav）的快速发展，现在可以以更经济的方式扫描大型站点。******提出的研究旨在为大规模3D场景重建开发新颖，高效和自主的技术。为了实现这一目标，在未来五年内，我和我的学生将研究：1)如何使用配备激光雷达的无人机进行大型户外场景的质量引导自主3D重建；2)如何使用仅具有图像捕获能力的低成本现成无人机实现相同的目标；3)让两种类型的无人机协同工作并融合图像和距离数据的好处；4)从点云中分割运动物体并重建运动物体动态四维时空模型的可行性。******随着VR设备的广泛应用，对大规模场景模型的需求预计会急剧增加。因此，在本研究中开发的技术将在上述领域产生广泛的影响，并使不同的研究团体受益。它们很可能通过使我们的城市和环境的高质量3D模型易于获得，推动信息系统和技术领域的发展。许多研究问题需要解决，这将有助于培训hqp在加拿大高科技行业中担任高要求的职位。

Monitors and TVs have been the dominating display devices in the past 30 years. They are only capable of showing 2D contents, which can be easily acquired using today's digital cameras. As virtual reality (VR) devices gain practicality and popularity, allowing users to view 3D contents from selected viewpoints and directions, an important question is, therefore, how to efficiently and economically capture objects and scenes in 3D.******The technology for acquiring 3D shapes of small objects is already mature. Users can scan a given object from different sides using a range scanner and then register together the 3D point clouds to generate a surface model. On this front, my collaborators and I have developed a state-of-the-art algorithm that automates the scanning process through positioning a scanner at strategically selected locations using a robotic arm. However, how to acquire high-quality models for large-scale outdoor scenes in an autonomous manner is still an open problem.******3D reconstruction for large sites has vast applications in areas such as urban planning, geological and archaeological survey, virtual tourism, and military simulation. It is an active topic in many research communities, including computer vision, graphics, robotics, civil engineering, and remote sensing. In the past, people often resorted to manned airborne LiDAR systems, which come with intimidating cost. Thanks to the rapid development of unmanned aerial vehicles (UAVs), it is now possible to scan large sites in a much more economical manner.******The proposed research aims at developing novel, efficient, and autonomous techniques for large-scale 3D scene reconstruction. To achieve this goal, in the next five years my students and I will investigate: 1) how to perform quality-guided autonomous 3D reconstruction for large outdoor scenes with LiDAR-equipped UAVs; 2) how to achieve the same objective using low-cost off-the-shelf UAVs with only image capture capability; 3) the benefits of letting both types of UAVs work collaboratively and fusing together image and range data; and 4) the feasibility of segmenting moving objects from point clouds and reconstructing dynamic 4D spatial-temporal models for these moving objects.******As VR devices get widely adopted, the demands for large-scale scene models are expected to increase dramatically. Hence, the techniques to be developed in this research will make broad impacts in aforementioned areas and benefit different research communities. They are likely to advance the Information Systems and Technology field through making high-quality 3D models of our cities and environments easily obtainable. A number of research questions need to be addressed, which will help to train HQPs to take up highly demanded positions in Canada's high tech industries.