@inproceedings{RuleML2015Poster, |
||
author |
= |
{Alexei A. Morozov and Olga S. Sushkova and Alexander F. Polupanov}, |
title |
= { |
An Approach to the Intelligent Monitoring of Anomalous Human Behaviour Based on the Actor Prolog Object-Oriented Logic Language}, |
editor |
= |
{N.Bassiliades and P.Fodor and A.Giurca and G.Gottlob and T.Kliegr and G.J.Nalepa and M.Palmirani and A.Paschke and M.Proctor and D.Roman and F.Sadri and N.Stojanovic}, |
booktitle |
= |
{{RuleML} 2015 {DC} and {C}hallenge. Proceedings of the 9th International {Rule Challenge} and the 5th {RuleML} Doctoral Consortium (Berlin, Germany, August 2-5)}, |
publisher |
= |
{CEUR}, |
address |
= |
{Berlin}, |
year |
= |
2015, |
url |
= |
"https://www.csw.inf.fu-berlin.de/ruleml2015-ceur", |
abstract |
= { |
A method for the monitoring of anomalous human behaviour that is based on the logical description of complex human behaviour patterns and special kinds of blob (a separated area of a foreground image) motion statistical metrics is developed. The concurrent object-oriented logic language is used for the analysis of graphs of tracks of moving blobs; the graphs are supplied by low-level analysis algorithms implemented in a special built-in class of Actor Prolog. The blob motion statistics is collected by the low-level analysis procedures that are of the need for the discrimination of running people, people riding bicycles, and cars in a video scene. The first-order logic language is used for implementing the fuzzy logical inference based on the blob motion statistics. A research software platform is developed that is based on the Actor Prolog logic language and a state-of-the-art Prolog-to-Java translator for experimenting with the intelligent visual surveillance. |
} |