Multipath Exploitation for Human Activity Recognition using a Radar Network

In this study, the problem of multipath in radar sensor networks for human activity recognition (HAR) has been examined. Traditionally considered as a source of additional clutter, the multipath is being investigated for its potential to be exploited through the creation of virtual radar nodes. These virtual nodes are conceptualized to...

Classification of Human Activities with Distributed Radar Systems

This thesis introduces the relevance of radar systems in the realm of human activity recognition (HAR) in Chapter 1. The study touches upon the complex understanding of continuous human activities and the existing challenges and gaps in current methodologies, hinting at the innovative technical approaches that are to be detailed in the following...

Physics-informed Data Augmentation for Human Radar Signatures

In recent years, neural networks (NNs) have seen a surge in popularity due to their ability to model complex patterns and relationships in data. One of the challenges of using NNs is the requirement for large amounts of labelled data to train the model effectively. In many real-world applications such as radar, labelled data may be scarce due to...

Angle-insensitive Human Motion and Posture Recognition Based on 2D FMCW MIMO Radar and Deep Learning Classifiers

Nowadays, the aging problem is shaking the root of the healthcare system in many countries, an automatic human activity recognition (HAR) is seen as a promising solution to that problem. In particular, radar-based HAR attracts people’s attention thanks to its respect for privacy and functionality in poor lighting conditions. With a lot of...

A Deep Learning Framework for Recognizing Both Static and Dynamic Gestures

Intuitive user interfaces are indispensable to interact with the human centric smart environments. In this paper, we propose a unified framework that recognizes both static and dynamic gestures, using simple RGB vision (without depth sensing). This feature makes it suitable for inexpensive human-robot interaction in social or industrial settings...

Machine Learning as Enabler of Design-to-Robotic-Operation

This essay promotes Artificial Intelligence (AI) via Machine Learning (ML) as a fundamental enabler of technically intelligent built-environments. It does this by detailing ML’s successful application within three deployment domains: (1) Human Activity Recognition, (2) Object as well as Facial-Identity and -Expression Recognition, and (3) Speech...