The Perfect Match: 3D Point Cloud Matching With Smoothed Densities
The Perfect Match: 3D Point Cloud Matching With Smoothed Densities
We propose 3DSmoothNet, a full workflow to match 3D point clouds with a siamese deep learning architecture and fully convolutional layers using a voxelized smoothed density value (SDV) representation. The latter is computed per interest point and aligned to the local reference frame (LRF) to achieve rotation invariance. Our compact, …