Online Probabilistic Interval-based Event Calculus

Mantenoglou P., Artikis A. and Paliouras G. - 24th European Conference on Artificial Intelligence (ECAI) - 2020


Activity recognition systems detect temporal combinations of ‘low-level’ or ‘short-term’ activities on sensor data. These systems exhibit various types of uncertainty, often leading to erroneous detection. We present an extension of an interval-based activity recognition system which operates on top of a probabilistic Event Calculus implementation. Our proposed system performs on-line recognition, as opposed to batch processing, thus supporting data streams. The empirical analysis demonstrates the efficacy of our system, comparing it to interval-based batch recognition, point-based recognition, as well as structure and weight learning models.

Go to publication:

This project has received funding from the European Union Horizon 2020 research and innovation programme under grant agreement No 825070.

Let's get in touch!