  Distributed surveillance systems have become popular in recent years due to
security concerns. However, transmitting high dimensional data in
bandwidth-limited distributed systems becomes a major challenge. In this paper,
we address this issue by proposing a novel probabilistic algorithm based on the
divergence between the probability distributions of the visual features in
order to reduce their dimensionality and thus save the network bandwidth in
distributed wireless smart camera networks. We demonstrate the effectiveness of
the proposed approach through extensive experiments on two surveillance
recognition tasks.
