CRII: RI: High-Speed Vision-Based Motion Estimation

设备运动估计是诸如移动机器人和虚拟或增强现实显示器等空间感知系统的关键组件。运动估计随时间的积分，或航位推算，通常用于在间歇性绝对位置测量之间跟踪设备在空间中的位置和方向。基于视觉的运动估计是一种被动的、低成本的方法，提供了高精度。该项目为基于视觉的运动估计开发了更快的方法。这项工作的动机是基本的洞察力，即提高运动估计的速度会导致系统改进的“良性循环”：通过更快地计算运动估计，相机可以以更高的速率操作；这反过来又导致连续帧之间的运动较少，从而实现更快的计算。在目前的前期工作中实现的加速依赖于两种技术：运动模型的近似；以及将基本几何问题简化为更小的形式，以便更快地求解。通过对相关问题的研究，PI试图确定能够以类似方式有效地解决的整个类别的视觉运动估计问题。

Device motion estimation is a key component of spatially-aware systems such as mobile robots and virtual or augmented reality displays. Integration of motion estimates over time, or dead reckoning, is typically used to track the position and orientation of the device in space between intermittent absolute position measurements. Vision-based motion estimation is a passive, low-cost approach that provides high accuracy. This project develops faster methods for vision-based motion estimation. The motivation for this work is the basic insight that increasing the speed of motion estimation leads to a "virtuous cycle" of system improvement: by computing the motion estimate more quickly, the camera can be operated a higher rate; this in turns leads to less motion between successive frames, enabling faster computations. The speedups achieved in the current preliminary work rely on two techniques: approximation of the motion model; and reduction of fundamental geometric problem to a smaller form which is quicker to solve. By investigating related problems, the PI seeks to determine an entire class of visual motion estimation problems which can be efficiently solved in a similar way.