Exploring the Practical Limits of Optical Flow

This report documents our experience with different optical flow estimation methods and our attempt to use optical flow both qualitatively and quantitatively. Special attention is devoted to improving the Lucas-Kanade method to obtain dense flow. We use a simple clustering technique to find looming objects. This method has the potential of supporting obstacle avoidance using optical flow. Experiments using real images demonstrate that this simple clustering is effective for certain scenes. We also point out when this technique will fail. We try to use optical flow quantitatively to recover the structure of a piecewise planar environment. First, we use the widely-known 8-parameter planar flow equations to locate individual planes in the scene. Second, in lieu of full flow, we try to use normal flow to compute both the ego-motion and the structure. Both trials fail ungracefully, mostly due to noisy flow data. We describe the mathematics ofboth methods and our experimental results