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

CRII：RI：基于高速视觉的运动估计

基本信息

批准号：
1464420
负责人：
Jonathan Ventura
金额：
$ 17.48万
依托单位：
University of Colorado at Colorado Springs
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2015
资助国家：
美国
起止时间：
2015-05-01 至 2020-04-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1464420&HistoricalAwards=false
关键词：
CRII RI Speed Vision Based

项目摘要

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.

设备运动估计是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成部分。运动估计随时间的积分或航位推算通常用于跟踪设备在间歇性绝对位置测量之间的空间中的位置和方向。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。这项工作的动机是这样的基本见解：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；这反过来又会减少连续帧之间的运动，从而实现更快的计算。当前初步工作中实现的加速依赖于两种技术：运动模型的近似；将基本几何问题简化为更小的形式，从而更快地解决。通过研究相关问题，PI 试图确定一整类可以通过类似方式有效解决的视觉运动估计问题。

项目成果

期刊论文数量（1）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Unsupervised Learning of Depth and Ego-Motion From Cylindrical Panoramic Video

DOI：
10.1109/aivr46125.2019.00018
发表时间：
2019-01
期刊：
2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)
影响因子：
0
作者：
Alisha Sharma;Jonathan Ventura
通讯作者：
Alisha Sharma;Jonathan Ventura