Ego-Motion Estimation Using Optical Flow Fields Observed from Multiple Cameras

In this paper, we consider a multi-camera vision system mounted on a moving object in a static threedimensional environment. By using the motion flow fields seen by all of the cameras, an algorithm which does not need to solve the point-correspondence problem among the cameras is proposed to estimate the 3D ego-motion parameters of the moving object. Our experiments have shown that using multiple optical flow fields obtained from different cameras can be very helpful for ego-motion estimation. 1 Introduction Three-dimensional ego-motion estimation has been one of the most important problems for the application of computer vision in mobile robots [10]. Accurate estimation of ego-motion is very helpful for human computer interaction and short-term control such as braking, steering, and navigation. In the past, there have been many methods [1, 6, 7, 12] which use flow vectors as the basis of their derivations for motion estimation. No matter their derivations are linear or nonlinear, the..