Deep Metric Learning on Point Sets for 3D Industry Elements Recognition

摘要

Point cloud is an important data type for representing the geometric characteristics of industry elements. Due to its irregular format, most researchers transform such data to regular 3D voxel grids or collections of images and apply existing mature deep learning framework on it. In this paper, we proposed a deep metric learning based network which projects point sets into embedding space to pull the intra-class samples closer and push the inter-class samples far away. To further facilitate the future research on this problem, a new dataset (Industry Element 8) containing 8 industry elements cloud point is built. Experimental results have demonstrated the superior performance of our proposed learning network.