To conveniently, quickly, and accurately obtain three-dimensional (3D) point clouds of a complete surface, this study proposes a coarse splicing method of multi-view point clouds based on the calibrated parameters of a turntable. The proposed method uses a two-dimensional calibration target as the switching hub of coordinate systems. A nonlinear model including the turntable rotating angle and different measuring coordinate systems is established by exclusively using the coordinate system's relationship at two positions. Coarse registration of 3D point clouds under multiple measurement angles provides a good initial value for the iterative closest point (ICP) algorithm and increases the robustness of the ICP algorithm. Experimental results show that the operation of this method is convenient, fast, and easy to implement. Additionally, the obtained splicing error of point clouds is less than 0.12 mm.