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arXiv · 1204.1851

A Probabilistic Logic Programming Event Calculus

Anastasios Skarlatidis·Alexander Artikis·Jason Filippou·Georgios Paliouras
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Abstract

We present a system for recognising human activity given a symbolic representation of video content. The input of our system is a set of time-stamped short-term activities (STA) detected on video frames. The output is a set of recognised long-term activities (LTA), which are pre-defined temporal combinations of STA. The constraints on the STA that, if satisfied, lead to the recognition of a LTA, have been expressed using a dialect of the Event Calculus. In order to handle the uncertainty that naturally occurs in human activity recognition, we adapted this dialect to a state-of-the-art probabilistic logic programming framework. We present a detailed evaluation and comparison of the crisp and probabilistic approaches through experimentation on a benchmark dataset of human surveillance videos.

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Anastasios Skarlatidis, Alexander Artikis, Jason Filippou, Georgios Paliouras. 2012-04-09. A Probabilistic Logic Programming Event Calculus. https://doi.org/10.1017/s1471068413000690

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