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3D pose estimation is an important part of 3D motion estimation, which is useful for visualized operation and control. The paper classified approaches of 3D pose estimation from a monocular image sequence into three types: feature-based approach, optical-flow-based approach and model-based approach. In feature-based approaches, 3D motion are estimated by observing a set of 2D features, such as points, lines, junctions and corners, over two or more images. On the contrary, optical-flow-based approaches estimate instantaneous 3D motion from image plane velocity. Both of them can complete the estimation without any a priori knowledge of the object, but the computation is complex and time-consuming. Mode-based approach avoids the burden of computation, but relies on the a priori knowledge of the object. Current research status of each approach is reviewed. Comparison of these three approaches and developing trends of 3D pose estimation are discussed in the conclusion.