This is visual odometry estimated directly from sparse optical flow using nearest neighbor learners. We train many (~80) learners, each on optical flow from four random locations in the image. At runtime, each learner votes on a visual odometry measurement if optical flow is well-defined in its image locations, and we choose the median estimate.