3D-Surface Reconstruction

3D 表面重建

基本信息

批准号：
200549338
负责人：
Professor Dr. Daniel Cremers
金额：
--
依托单位：
Lehrstuhl für Photogrammetrie
依托单位国家：
德国
项目类别：
Research Units
财政年份：
2011
资助国家：
德国
起止时间：
2010-12-31 至 2018-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/200549338?language=en
关键词：
3D Surface Reconstruction

项目摘要

The focus of P5 is the estimation of dense and high-resolution 3D reconstruction from the available image data. To this end, we pursue a two-stage strategy:(1) Based on the onboard stereo camera, we aim at computing a crude semi-dense visual SLAM (depth maps, geometry and camera motion). It is computed at video frame rate on the quadrotor and takes into account the statistical uncertainty of 3D locations and image information.(2) On the ground station, we improve the semi-dense 3D reconstruction toward a high-resolution dense 3D reconstruction by also taking into account the high-resolution images from the main sensor. More specifically we plan to generate dense depth maps which are then fused to a dense 3D model. This step will also take into account 3D point clouds from bundle adjustment and 3D point clouds from the laser scanner. In this second phase of the project, we will emphasize robustness to perturbations through reflections, homogeneous surfaces and over-exposure.A central advantage of this two-stage strategy is that we will have a rudimentary self-localization and semi-dense 3D reconstruction of the scene computed onboard in a manner that does not depend on the communication with the ground station.The resulting semi-dense 3D reconstruction can for example be used for an adaptive viewpoint planning: During the flight, the system can immediately identify for which locations it has not obtained sufficient visual information yet. This information can in turn be used to adapt the flight trajectory so as to assure an optimal exploration of unknown territory.

P5的重点是从可用图像数据中估算了密集和高分辨率3D重建的估计。为此，我们采取了两阶段的策略：（1）基于机上立体声摄像机，我们旨在计算粗制的半密集视觉量（深度图，几何和相机运动）。它是在四个四面体上以视频帧速率计算的，并考虑了3D位置和图像信息的统计不确定性。（2）在地面站上，我们通过同时考虑了从主传感器的高分辨率图像来改善对高分辨率密集3D重建的半密集3D重建。更具体地说，我们计划生成密集的深度图，然后将其融合到密集的3D模型中。此步骤还将考虑到捆绑扫描仪的束调整和3D点云的3D点云。在项目的第二阶段中，我们将通过反思，均匀表面和过度暴露来强调对扰动的鲁棒性。这种两阶段策略的核心优势是，我们将具有基本的自定位和半密度的自定位和半密度的3D重建场景的重建，而不是在船上进行的典型范围，该示例不依赖于与地面站的相互作用。观点计划：在飞行过程中，系统可以立即确定其尚未获得足够的视觉信息的位置。此信息又可以用来适应飞行轨迹，以确保对未知区域的最佳探索。

项目成果

期刊论文数量（6）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

LDSO: Direct Sparse Odometry with Loop Closure

DOI：
10.1109/iros.2018.8593376
发表时间：
2018-01-01
期刊：
2018 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
影响因子：
0
作者：
Gao, Xiang;Wang, Rui;Cremers, Daniel
通讯作者：
Cremers, Daniel

Direct Visual-Inertial Odometry with Stereo Cameras

DOI：
10.1109/icra.2016.7487335
发表时间：
2016-01-01
期刊：
2016 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA)
影响因子：
0
作者：
Usenko, Vladyslav;Engel, Jakob;Cremers, Daniel
通讯作者：
Cremers, Daniel

Large-Scale Direct SLAM for Omnidirectional Cameras

DOI：
10.1109/iros.2015.7353366
发表时间：
2015-01-01
期刊：
2015 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
影响因子：
0
作者：
Caruso, David;Engel, Jakob;Cremers, Daniel
通讯作者：
Cremers, Daniel

Large-Scale Direct SLAM with Stereo Cameras

DOI：
10.1109/iros.2015.7353631
发表时间：
2015-01-01
期刊：
2015 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
影响因子：
0
作者：
Engel, Jakob;Stueckler, Joerg;Cremers, Daniel
通讯作者：
Cremers, Daniel

The Double Sphere Camera Model