Fusing multiple video sensors for surveillance

Abstract

Real-time detection, tracking, recognition, and activity understanding of moving objects from multiple sensors represent fundamental issues to be solved in order to develop surveillance systems that are able to autonomously monitor wide and complex environments. The algorithms that are needed span therefore from image processing to event detection and behaviour understanding, and each of them requires dedicated study and research. In this context, sensor fusion plays a pivotal role in managing the information and improving system performance. Here we present a novel fusion framework for combining the data coming from multiple and possibly heterogeneous sensors observing a surveillance area.