论文标题
使用未校准的多摄像机系统，对运动的结构进行约束束调整
Constrained Bundle Adjustment for Structure From Motion Using Uncalibrated Multi-Camera Systems
论文作者
论文摘要
使用未校准的多相机系统进行运动的结构是一项具有挑战性的任务。本文提出了一个捆绑调整解决方案，该解决方案实现了基线约束，尊重这些相机是彼此静态的。我们假设这些摄像机安装在移动平台上，未校准，并精巧同步。为此，我们提出了针对摄像机具有重叠视图的场景制定的基线约束。约束结合在束调整解决方案中，以保持不同相机静态的相对运动。使用安装在没有系统校准的车辆上的两个共处的GoPro摄像机的视频帧进行实验。将这两个摄像机放置在捕获重叠内容的情况下。我们使用建议的约束进行了捆绑调整，然后产生了3D密集的点云。通过将这些致密点云与激光雷达参考数据进行比较来进行评估。我们表明，与传统的捆绑调整相比，我们提出的方法提高了29.38％。
Structure from motion using uncalibrated multi-camera systems is a challenging task. This paper proposes a bundle adjustment solution that implements a baseline constraint respecting that these cameras are static to each other. We assume these cameras are mounted on a mobile platform, uncalibrated, and coarsely synchronized. To this end, we propose the baseline constraint that is formulated for the scenario in which the cameras have overlapping views. The constraint is incorporated in the bundle adjustment solution to keep the relative motion of different cameras static. Experiments were conducted using video frames of two collocated GoPro cameras mounted on a vehicle with no system calibration. These two cameras were placed capturing overlapping contents. We performed our bundle adjustment using the proposed constraint and then produced 3D dense point clouds. Evaluations were performed by comparing these dense point clouds against LiDAR reference data. We showed that, as compared to traditional bundle adjustment, our proposed method achieved an improvement of 29.38%.
