Panoramic Visual Odometry for Ground Vehicle

Motion estimation from image sensors is becoming an important component of navigation systems. The idea of making a low-cost, compact and self-contained device on vision attracts many researchers. We present our recent results on visual odometry using a panoramic camera in our unmanned ground vehicle. We exploit scanline intensity profiles to estimate the rotation by comparing their absolute difference. We transform the panoramic images into orthographic top view images, and perform feature detection to extract lanes and other manmade markers, then utilize the markers to estimate the horizontal speed. With the rotation and speed data, we determine the trajectory of the vehicle, and synthesise an orthographic top view image of the road plane along the trajectory. Finally, we verify our visual odometry system by experiment.