We present a new solution to tracking and mapping with an event camera. The motion of the camera contains both rotation and translation, and the displacements happen in an arbitrarily structured environment. As a result, the image matching may no longer be represented by a low-dimensional homographic warping, thus complicating an application of the commonly used Image of Warped Events (IWE). We introduce a new solution to this problem by performing contrast maximization in 3D. The 3D location of the rays cast for each event is smoothly varied as a function of a continuous-time motion parametrization, and the optimal parameters are found by maximizing the contrast in a volumetric ray density field. Our method thus performs joint optimization over motion and structure. The practical validity of our approach is supported by an application to AGV motion estimation and 3D reconstruction with a single vehicle-mounted event camera. The method approaches the performance obtained with regular cameras, and eventually outperforms in challenging visual conditions.
翻译:我们提出了一个用事件相机跟踪和绘图的新解决方案。 相机的动作包含旋转和翻译, 且迁移发生在任意结构化的环境中。 因此, 图像匹配可能不再以低维的全景扭曲为代表, 从而使得常用的扭曲事件图像( IWE)的应用复杂化。 我们通过在 3D 中进行对比最大化, 引入了这一问题的新解决方案。 每场事件所投射的3D射线的位置随着连续时间运动的平衡功能而变化顺利, 而最佳参数则通过在体积射线密度范围内最大限度地实现对比而找到。 因此, 我们的方法对运动和结构进行了联合优化。 我们的方法的实际有效性得到AGV运动估计应用程序的支持, 3D 重建时使用一个单一的车辆挂载事件相机。 这种方法接近了正常的摄像头, 最终在挑战性视觉条件下的超模。