Lucia Innocenti
Audio-Visual Human Activity Recognition for Humanoid Robotics.
Rel. Barbara Caputo. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2022
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Abstract
Recent advances in Robotics research are pushing the limits of machines toward faster, smarter, and more efficient devices. Notable results have been achieved from and hardware point of view, with humanoid devices that are able to consistently outperform human movements. From a perception perspective, however, we are still far from being capable to match human skills. The gap is even more consistent when we introduce constraints typical of on-board implementations, such as limited resources and real-time requirements, which leads to models that potentially work perfectly on a theoretical scenario, but are not deployable in real applications. Among the others, one of the most important tasks that a humanoid robot should implement correctly to enable a fruitful human-robot interaction is accurate human activity recognition, namely the identification, online, of the action that the human is performing, with the goal of triggering a consequent action,e.g.
to support the task
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