Point Cloud Instance Segmentation Method Based on Superpoint Graph

Abstract:

A point cloud instance segmentation method based on superpoint graph(ISPG) is proposed in this paper. The correlation between the adjacent points of point cloud objects is extracted based on superpoint graph structure. Then, the scene scanned by a sensor is divided into uniform geometric elements to represent the point cloud classes with same attributes. Finally, a graph convolution network is used to implement instance segmentation. It is shown that the method has an accuracy of 48.9% on Stanford’s large 3D indoor spatial dataset S3DIS when the IoU threshold is 0.5.