Human Activity Recognition from Real-World Depth Images
Master Practical Training Project/ Master’s thesis Status: available Supervisors: Irene Ballester, Martin Kampel Problem Statement Human Activity Recognition (HAR) in computer vision, a pivotal area for healthcare, security, and robotics, often relies on privacy-invading RGB cameras. To enhance HAR accuracy while safeguarding privacy, this project employs deep neural networks (GNN, CNN, transformers) with point clouds or … Continue reading Human Activity Recognition from Real-World Depth Images