On-line – February 19, 2021 – 4pm-5pm CET
Abstract of the talk
Human activity recognition has attracted enormous research interest because it provides precious contextual information in several domains spanning from health-care to security, safety, and entertainment. So far, robust and consolidated literature focused on the automatic detection of activities performed by single individuals, with a great variety of approaches in terms of sensing modalities, recognition techniques, specific set of recognized activities, and final application objectives. However, much less research attention has been devoted to scenarios in which multiple subjects perform individual or joint activities forming groups to achieve common goals. This problem is often referred as multi-user activity recognition. With the advent of the Internet-of-Things, smart objects are being pervasively spread in the environment and worn on the human body, enabling contextual and distributed recognition of group and multi-user activities. This talk discusses motivations and advantages of multi-user activity recognition and overviews sensing methods (including those based on Wearable Computing Systems and in particular Collaborative Body Sensor Networks), recognition approaches, and impact in practical, relevant applications. The discussion also outlines important open research challenges and related future directions.