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

University Of Colorado At Colorado Springs, Colorado Springs CO

Investigators

Abstract

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.