The Lucas-Kanade method is a widely-used algorithm in computer vision for optical flow estimation, which assumes that the flow is essentially constant in a small neighborhood of the pixel under consideration, allowing it to solve for motion vectors using a least-squares approach. This method is particularly effective for small motions and operates under the assumption of brightness constancy, spatial coherence, and temporal persistence.