Efficient Feature Distribution for Object Matching in Visual-Sensor Networks

In this paper, we propose a framework of hierarchical feature distribution for object matching in a network of visual sensors. In our approach, we hierarchically distribute the information in such a way that each individual node maintains only a small amount of information about the objects seen by the network. Nevertheless, this amount is sufficient to efficiently route queries through the network without any degradation of the matching performance. A set of requirements that have to be fulfilled by the object-matching method to be used in such a framework is defined. We provide examples of mapping four well-known, object-matching methods to a hierarchical feature-distribution scheme. The proposed approach was tested on a standard COIL-100 image database and in a basic surveillance scenario using our own distributed network simulator. The results show that the amount of data transmitted through the network can be significantly reduced in comparison to naive feature-distribution schemes such as flooding.