提出了一种基于稀疏光流场计算三维运动和结构的线性新方法，该方法综合视觉运动分析中的两类处理方法，选取图象中的角点作为特征点 ;并检测和跟踪图象序列中的角点.记录检测到的角点在图象序列中的位移，在理论上证明了时变图象的光流场可以近似地用角点的位移场代替，从而得到时变图象的稀疏光流场 ;通过光流运动模型的建立，推导出由稀疏光流场重建三维物体运动和结构的线性方法.通过用真实图象序列验证该算法，表明该算法取得了较好的效果

A new method to determine 3D motion and structure based on spare optical flow is presented. Motion analysis can be roughly classified as feature based or flow based, according to if the data they use are a set of features matches or an optical flow field. The proposed method integrates feature based and flow based method by using the corner points as feature points and estimating sparse optical flow field. Firstly, detecting and tracking corner points in image sequence and the locations of tracked corner points were recorded. Then, we proved that optical flow field could be replaced using displacement field approximately in theoretically, so the optical flow field was estimated at sparse locations by measuring the displacement of corner points between consecutive frames. Finally, a new linear method is derived to determine the 3D motion and structure at each corner point from known optical flow field. Experimental results using real image sequences showed that the presented method provided a good estimation of the optical flow field and 3D motion and structure.