Services on Demand
Journal
Article
Indicators
- Cited by SciELO
- Access statistics
Related links
- Similars in SciELO
Share
Computación y Sistemas
On-line version ISSN 2007-9737Print version ISSN 1405-5546
Abstract
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 2007-9737.
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.
Keywords : Machine vision; real-time systems; unusual activity detection; automatic surveillance.