360° detection and tracking algorithm of both pedestrian and vehicle using fisheye images
June 4, 2015 in Publications, year 4
Massimo Bertozzi, Luca Castangia, Stafano Cattani, Antonio Prioletti, and Pietro Versari
IEEE Intelligent Vehicles Symposium 2015 (IV2015)
All-around view is a mandatory element for autonomous vehicles. The European V-Charge project seeks to develop an autonomous vehicle using only low-cost sensors. This paper presents a detection and tracking algorithm that covers all the area around the vehicle using 4 fisheyecameras only. The algorithm is able to detect pedestrians and vehicles and track them, using cylindrical images. This paper presents the whole pipeline, from the image un-warping to the classification and the tracking algorithms, together with some results.
@inproceedings{iv2015v-charge,
author="Massimo Bertozzi AND Luca Castangia AND Stefano Cattani AND Antonio Prioletti AND Pietro Versari",
title="{360$^\circ$ Detection and Tracking Algorithm of both Pedestrian and Vehicle using Fisheye images}",
booktitle = "Procs.~IEEE Intelligent Vehicles Symposium 2015",
year=2015,
address = "Seoul, Korea",
month=jun
}





This paper presents a monocular algorithm for front and rear vehicle detection, developed as part of the FP7 V-Charge project’s perception system. The system is made of an AdaBoost classifier with Haar Features Decision Stump. It processes several virtual perspective images, obtained by un-warping 4 monocular fish-eye cameras mounted all-around an autonomous electric car. The target scenario is the automated valet parking, but the presented technique fits well in any general urban and highway environment. A great attention has been given to optimize the computational performance. The accuracy in the detection and a low computation costs are provided by combining a multiscale detection scheme with a Soft-Cascade classifier design. The algorithm runs in real time on the project’s hardware platform.

