Geometric features for voxel-based surface recognition
This work addresses surface recognition for CAD applications, but it is incremental as it builds on existing geometric features and methods.
The authors tackled the problem of CAD surface recognition by introducing a library of geometric voxel features, including local intrinsic volumes and aggregated Haar wavelet features, and demonstrated accurate object classification on the ESB dataset using shallow decision trees.
We introduce a library of geometric voxel features for CAD surface recognition/retrieval tasks. Our features include local versions of the intrinsic volumes (the usual 3D volume, surface area, integrated mean and Gaussian curvature) and a few closely related quantities. We also compute Haar wavelet and statistical distribution features by aggregating raw voxel features. We apply our features to object classification on the ESB data set and demonstrate accurate results with a small number of shallow decision trees.