论文标题
单眼旋转式循环旋转和循环平均和循环闭合
Monocular Rotational Odometry with Incremental Rotation Averaging and Loop Closure
论文作者
论文摘要
估计绝对相机方向对于态度估计任务至关重要。一种已建立的方法是首先执行视觉探光（VO）或视觉大满贯（V-SLAM），并从VO或V-Slam估计的相机姿势（6 DOF）中检索相机方向（3 DOF）。除了估计完整6 DOF相机姿势的冗余之外，这种方法的一个缺点是，由于对结构和运动的基本约束，依赖于与6 DOF姿势共同估算地图（3D场景点）的依赖性。为了简化绝对方向估计的任务，我们制定了单眼旋转探空仪问题，并设计了快速算法以仅使用2D-2D功能匹配来准确估算摄像机方向。基础我们的系统是一种新的增量旋转平均方法，用于快速，恒定的时间迭代更新。此外，我们的系统还保留了一个视图图1）允许求解循环闭合以删除相机方向漂移，2）可以使用温暖启动V-SLAM系统。我们在现实世界数据集上进行了广泛的定量实验，以证明我们增量相机方向求解器的准确性。最后，我们展示了算法对V-Slam的好处：1）解决已知的旋转问题以估计相机和周围地图的轨迹，以及2）使V-Slam系统能够跟踪纯旋转运动。
Estimating absolute camera orientations is essential for attitude estimation tasks. An established approach is to first carry out visual odometry (VO) or visual SLAM (V-SLAM), and retrieve the camera orientations (3 DOF) from the camera poses (6 DOF) estimated by VO or V-SLAM. One drawback of this approach, besides the redundancy in estimating full 6 DOF camera poses, is the dependency on estimating a map (3D scene points) jointly with the 6 DOF poses due to the basic constraint on structure-and-motion. To simplify the task of absolute orientation estimation, we formulate the monocular rotational odometry problem and devise a fast algorithm to accurately estimate camera orientations with 2D-2D feature matches alone. Underpinning our system is a new incremental rotation averaging method for fast and constant time iterative updating. Furthermore, our system maintains a view-graph that 1) allows solving loop closure to remove camera orientation drift, and 2) can be used to warm start a V-SLAM system. We conduct extensive quantitative experiments on real-world datasets to demonstrate the accuracy of our incremental camera orientation solver. Finally, we showcase the benefit of our algorithm to V-SLAM: 1) solving the known rotation problem to estimate the trajectory of the camera and the surrounding map, and 2)enabling V-SLAM systems to track pure rotational motions.
