关键词: 点云数据, 表示方法, 深度学习, 八插树, K-D树

Abstract:

A point cloud data representation method based on the octree tree and K-D tree is proposed to realize end to end representation point cloud model in deep learning. This method transforms the unorganized point cloud into a voxel space, and uses the octree model to divide and improves octree coding method. The adjacency relationship between nodes is constructed, and the octree is constructed in parallel on the GPU. A 3D K-D tree is used to index a single 3D spatial point in order to overcome the inefficiency of octree coding retrieval. Experimental results show that the method can truly reflect the details of the model itself and improve the construction time and retrieval efficiency of point cloud model. The new data structure transforms the point cloud into a form of data that can be received by convolutional neural network.

Key words: point cloud data, representation method, deep learning, octreetree, K-D tree