Ambient-Assisted-Living

Modern service robots are provided with one or more sensors, often including RGB-D cameras, to perceive objects and humans in the …

We investigate how incremental learning of long-term human activity patterns improves the accuracy of activity classification over …

The paper presents a probabilistic approach using spatio-temporal and social features to recognize human-human interaction activities, learns priors based on proxemics theory to improve classification, and provides a new public RGB-D dataset of social activities including risk situations, with results showing the proposed method merging different features and proximity priors improves precision, recall and accuracy over alternative approaches