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

设备运动估计是诸如移动的机器人和虚拟或增强现实显示器的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装置在空间中的位置和定向。基于视觉的运动估计是一种被动、低成本的方法，可提供高精度。该项目开发了更快的基于视觉的运动估计方法。这项工作的动机是基本的见解，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运行;这反过来又会导致连续帧之间的运动减少，从而实现更快的计算。在目前的初步工作中实现的加速依赖于两种技术：近似的运动模型;和减少的基本几何问题，以更快地解决一个更小的形式。通过调查相关的问题，PI试图确定一整类的视觉运动估计问题，可以有效地解决类似的方式。

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.