An audio-visual sensor fusion approach for feature based vehicle identification

Abstract

In this article we present our software framework for embedded online data fusion, called I-SENSE. We discuss the fusion model and the decision modeling approach using support vector machines. Due to the system complexity and the genetic approach a data oriented model is introduced. The main focus of the article is targeted at our techniques for extracting features of acoustic-and visual-data. Experimental results of our "traffic surveillance" case study demonstrate the feasibility of our multi-level data fusion approach.