3 accepted papers
Human Activity Recognition supports applications in healthcare, manufacturing, and human-machine interaction. LiDAR point clouds offer a privacy-preserving alternative to cameras and are robust to illumination. We propose a HAR method based on graph spectral analysis. Each LiDAR frame is mapped to a…
Training deep learning models for point cloud prediction tasks such as shape completion and generation depends critically on loss functions that measure discrepancies between predicted and ground-truth point sets. Commonly used functions such as Chamfer Distance (CD), HyperCD, InfoCD and Density-awa…
Feature selection is one of the most important and widely-used dimension reduction techniques due to its efficiency and intractability of the results. In this paper, we propose a simple but efficient unsupervised feature ranking and selection method by exploiting the geometry of the original feature…