%\section{Conclusion}
%\label{sec:conclusion}
%
%We have introduced a novel active learning framework for video annotation.  Our
%algorithm is unique compared to contemporary active learning approaches because
%we wish to most efficiently annotate a \emph{single label} and not learn an
%entire model. By intelligently spending clicks on difficult parts of the label,
%we demonstrate a significant boost over a fixed rate tracker given a fixed
%budget.  Indeed, our approach would be able to annotate the VIRAT data set for
%a fraction of its original cost. We hope the findings in this paper will spark
%the construction of massive, labeled video databases and enable continued
%research in data-driven computer vision applications.
