Joint Acoustic-Video Fingerprinting of Vehicles, Part I

We address vehicle classification and measurement problems using acoustic and video sensors. In this paper, we show how to estimate a vehicle´s speed, width, and length by jointly estimating its acoustic wave-pattern using a single passive sensor that records the vehicle´s drive-by noise. The acoustic wave-pattern is approximated using three envelope shape (ES) components, which approximate the shape of the received signal´s power envelope. We incorporate the parameters of the ES components along with the estimates of the vehicle engine RPM and number of cylinders to create a vehicle profile vector that forms an intuitive discriminatory feature space. In the companion paper, we discuss vehicle classification and mensuration based on silhouette extraction and wheel detection, using a video sensor. Vehicle speed estimation and classification results are provided using field data.