\chapter{Video annotation using ontologies and rule learning}\label{chap:rules}
{

\begin{quote}
\textit{In this chapter we present an approach for automatic annotation and retrieval of video content, based on ontologies and semantic concept classifiers. A novel rule-based method is used to describe and recognize composite concepts and events. Our algorithm learns automatically rules expressed in Semantic Web Rules Language (SWRL), exploiting the knowledge embedded into the ontology. The relationship between concepts, their co-occurrence and the temporal consistency of video data are used to improve the performance of individual concept detectors. Finally, we present a web video search engine, based on ontologies, that permits queries using a composition of boolean and temporal relations between concepts.
\footnote{This chapter has been published as \dquote{Video Annotation and Retrieval Using Ontologies and Rule Learning} in \textit{IEEE MultiMedia, vol.~17, iss.~4, pp.~80-88, 2010}~\cite{ballan-mmul10}.}
}
\end{quote}


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\section{Introduction}


%-------------------------------------------------------------------------
\section{Related work}


%-------------------------------------------------------------------------
\section{Automatic rule learning using first order logic}\label{sec:foils}

\subsection{Improving performance}

\subsection{Rule learning example}


%-------------------------------------------------------------------------
\section{Experimental results}\label{sec:experiments8}


%-------------------------------------------------------------------------
\section{The {S}irio web-based search engine}\label{sec:retrieval8}
 

%-------------------------------------------------------------------------
\section{Conclusion}\label{sec:conclusion8}

}