Computación y Sistemas
versión impresa ISSN 1405-5546
CANCHOLA MAGDALENO, Sandra Luz et al. A Machine-Vision System to Detect Unusual Activities Online at Vehicular Intersections. Comp. y Sist. [online]. 2009, vol.13, n.2, pp. 209-220. ISSN 1405-5546.
In this article, we present a real-time machine-vision system to detect vehicles running on red light or performing forbidden turns at crossroads. The system operates during daytime by receiving video streams from two different sources. One of them is a camera viewing the crossroads to detect unusual activity, while a second camera watches the semaphore to keep synchrony with the traffic controller. The system performance and reliability have been tested on a real vehicular intersection during extended periods of time.
Palabras llave : Machine vision; real-time systems; unusual activity detection; automatic surveillance.