Parameterization of Acoustic Signatures in Ultrasound Images for the Detection of Human Presence by Autonomous Vehicles
Paper in proceedings, 2010
We address the problem of human detection for autonomous
vehicles. Instead of using an optical system, we propose to
employ an acoustic 2D array to reliably obtain an image of a
human in a 3D spatial power spectrum which is independent
of lighting conditions and uses cheap ultrasound sensors.
We show that humans have a distinct acoustic signature and
propose to model the echoes from reflecting parts of objects
in the scene by a Gaussian-Mixture-Model. When the model is fitted to the acoustic image, it is straightforward to
obtain geometric relations between the present echoes and
represent the acoustic signatures in a low-dimensional parameter space. We present results based on real data measurements that demonstrate that different objects can be reconstructed from the data and discriminated. The obtained
parameter space can then be the basis for subsequent detection and classification of humans.