3D reconstruction is the transformation of real objects into mathematical models. By using 3D models, we can observe the shape and measure the parameters, and help us to analyze the properties of objects. For the problems of incompleteness and inefficiency in the reconstruction of object 3D point clouds, a fast and automated system for panoramic 3D point cloud reconstruction of objects was proposed. First, we designed an automatic platform, which could acquire RGB image sequences of objects in two directions. Then we adopted the Structure From Motion (SFM) algorithm to generate point clouds. For the problem of different scales of point clouds, we obtained the scaling by calculating the length ratio of the axes of the oriented bounding box, and scaled the point clouds to a uniform scale. In addition, markers were placed around the object and used to acquire the rotation matrix of the object point cloud in two directions. Finally, we verified the point cloud models of different objects generated by the system, and found that the relative error didn't exceed 6.67%. According to the results, the system proposed could reconstruct the panoramic 3D point cloud of the object better and provide a reference for related research.