Radar-Based Robust People Tracking and Consumer Applications
Alexandros Ninos, Jürgen Hasch, Michael Heizmann, Thomas Zwick
Abstract
Robust people tracking in an indoor or outdoor environment is an important feature for fitness applications, surveillance systems for security, and assisted living for the elderly. Camera-based systems offer the state of the art approach but raise privacy concerns and consume a significant amount of power for the sensor and the processing. On the other hand, modern millimeter-wave Radar sensors provide a low-cost and low-power alternative with very good resolution in range, radial velocity and angle of arrival. In this work, we use two popular algorithms, for tracking people using Radar, and compare them with our novel method. We show that our method is robust in certain corner cases and is suitable for scenarios with many users in close proximity. In addition, we present two consumer applications that are possible with a Radar system, multi-user macro gesture recognition and hand tracking. We believe that the combination of above methods will open new gateways for consumer applications.