论文标题
PatchMatch-Stereo-Panorama，360°视频图像的快速密集重建
PatchMatch-Stereo-Panorama, a fast dense reconstruction from 360° video images
论文作者
论文摘要
这项工作提出了一种新的方法，用于用于常见的360°动作凸轮实时密集的3D重建，该方法可以安装在USAR任务期间的小型侦察无人机上。所提出的方法通过添加一个附加的致密性线程，该额外的致密线程通过patch-match-stereo-apprace来扩展基于特征的视觉单眼大满贯（基于流行的ORB-SLAM），以在等应角视频输入上进行稳健的长期定位，该额外的致密线程与任何给定的密钥帧相对于任何给定的密钥帧的密集对应。算法算法的贴片示意图被认为是大规模mutli-view-stereo的艺术状态，但到目前为止，他们尚未针对实时密集的3D重建任务进行调整。这项工作描述了一个新的大规模并行变体，该变量是贴片示意图 - 算法与当前方法不同的两种方式：首先，它支持等效的摄像头模型，而其他解决方案仅限于针孔摄像机模型。其次，它是针对低潜伏期进行了优化的，同时保持高水平的完整性和准确性。为此，它仅在钥匙扣的小序列上运行，但采用技术来补偿由于帧数有限而导致的准确性损失。结果表明，使用最近移动GPU的消费级笔记本电脑上可以进行密集的3D重建，并且可以提高准确性和完整性，而与常见的离线MVS解决方案具有可比的质量设置相比。
This work proposes a new method for real-time dense 3d reconstruction for common 360° action cams, which can be mounted on small scouting UAVs during USAR missions. The proposed method extends a feature based Visual monocular SLAM (OpenVSLAM, based on the popular ORB-SLAM) for robust long-term localization on equirectangular video input by adding an additional densification thread that computes dense correspondences for any given keyframe with respect to a local keyframe-neighboorhood using a PatchMatch-Stereo-approach. While PatchMatch-Stereo-types of algorithms are considered state of the art for large scale Mutli-View-Stereo they had not been adapted so far for real-time dense 3d reconstruction tasks. This work describes a new massively parallel variant of the PatchMatch-Stereo-algorithm that differs from current approaches in two ways: First it supports the equirectangular camera model while other solutions are limited to the pinhole camera model. Second it is optimized for low latency while keeping a high level of completeness and accuracy. To achieve this it operates only on small sequences of keyframes, but employs techniques to compensate for the potential loss of accuracy due to the limited number of frames. Results demonstrate that dense 3d reconstruction is possible on a consumer grade laptop with a recent mobile GPU and that it is possible with improved accuracy and completeness over common offline-MVS solutions with comparable quality settings.
