Aiming at the problem of efficient target 3D point cloud segmentation in polarization-modulated 3D imaging system, an efficient segmentation concept of multi-dimensional information fusion is proposed. The system uses a high-resolution EMCCD camera as a planar array detector, during an imaging cycle, the gray image in the field-of-view and the 3D point cloud data can be obtained simultaneously. According to the imaging characteristics, the point-to-point mapping relationship between pixel coordinates of gray image and pixel coordinates of point cloud data is established. Combining with the image edge segmentation method by using particle swarm optimization algorithm, the coordinate information of the target after segmentation is mapped to the 3D point cloud data, so its 3D point cloud data is obtained. In this method, 3D point cloud data processing is reduced to 2D image processing, which significantly reduces the computational complexity and avoids the influence of distance noise on segmentation accuracy. The effectiveness of the method is verified by experiments.