Alessandro Bevilacqua
University of Bologna
ARCES-DEIS (Department of Electronics, Computer Science and
Systems) - Viale Risorgimento, 2
40136 Bologna
ITALY
| e-mail:
abevilacqua@deis.unibo.it |
http:// |
Keywords: parameter optimization, genetic
algorithm, motion analysis, motion detection, visual surveillance,
background difference, traffic monitoring
Abstract
Visual surveillance and monitoring
have aroused interest in the computer video community for many
years. The main task of these applications is to identify (and
track) moving targets. The traffic monitoring application we have
developed requires that a large number of parameters is tuned in
order to work properly. About thirty parameters concerning the
detection algorithm have been considered as to be optimized.
Accordingly, this paper shows how a Genetic Algorithm (GA)
represents a powerful task in order to automatically compute sub-optimal
parameter settings in a motion detection system. Besides, to our
knowledge this work is the first attempt of using GAs to such a
problem. Accurate experiments accomplished on a challenging test
sequence show the relevant results attained in terms of
qualitative performance.