We have been developing 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 detected on video frames. The output of our system is a set of recognised long-term activities, which are pre-defined temporal combinations of short-term activities. The constraints on the short-term activities that, if satisfied, lead to the recognition of a long-term activity, are expressed using a dialect of the Event Calculus. We illustrate the expressiveness of the dialect by showing the representation of several typical complex activities. Furthermore, we present a detailed evaluation of the system through experimentation on a benchmark dataset of surveillance videos.
@article{arxiv.0905.4614,
title = {A Logic Programming Approach to Activity Recognition},
author = {A. Artikis and M. Sergot and G. Paliouras},
journal= {arXiv preprint arXiv:0905.4614},
year = {2013}
}
Comments
The original publication is available in the Proceedings of the 2nd ACM international workshop on Events in multimedia, 2010