A probabilistic logic programming event calculus

Anastasios Skarlatidis ((1) and Institute of Informatics and Telecommunications, NCSR Demokritos, Athens, Greece)
Alexander Artikis (1)
Jason Filippou ((1) and University of Maryland, USA)
Georgios Paliouras (1)

(1) Institute of Informatics and Telecommunications, NCSR Demokritos, Athens, Greece


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.


Bibtex (Use it for references)

journal = {Theory and Practice of Logic Programming},
publisher = {Cambridge University Press},
author = {Anastasios Skarlatidis and Alexander Artikis and Jason Filippou and Georgios Paliouras},
title = {A probabilistic logic programming event calculus},
volume = {15},
number = {2},
year = {2015},
pages = {213 – 245}

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