Multi-subject human activities: A survey of recognition and evaluation methods based on a formal framework
Luca Arrotta, Gabriele Civitarese, Xi Chen, Julien Cumin, Cláudio Bettini · Expert Systems with Applications · 2024
Human Activity Recognition (HAR) in smart environments is a well-explored research domain, given its diverse applications which include healthcare, surveillance, building management, and many more. While the majority of HAR research focuses on recognizing the activities of a single subject, in real-world scenarios smart environments are often populated by multiple subjects that may be engaged in both independent and joint activities. This gives rise to the challenge of Multi-Subject HAR, which is an open and complex problem. This survey paper aims to offer researchers and practitioners a comprehensive analysis of Multi-Subject HAR, encompassing its potential applications, sensing solutions, methods, datasets, evaluation metrics, and ongoing challenges. In addition to presenting the latest research works in this area and identifying open issues, our major contributions consist of a comprehensive problem formalization and a thorough discussion of the evaluation metrics to assess different dimensions of multi-subject HAR systems. • We provide a comprehensive formalization for multi-subject HAR in smart environments. • We review the latest research works and datasets in this area. • We explore evaluation metrics and dataset-splitting strategies.