Personnel Detection via Fusion of Heterogeneous Sensor Data

摘要

The aim of this project was to (i) detect and classify personnel and their activities in an indoor environment monitored by different sensors, and (ii) develop novel signal processing approaches for networked sensors. During the course of this project, we have considered the case of video surveillance and have shown improved tracking performance using quality based fusion of data from multiple video sensors. We developed a copula based approach to heterogeneous sensor fusion.