Conference/ProceedingsIEEE Workshop on Applications of Computer Vision (WACV)
Start date05.01.2011
End date07.01.2011
AddressKona, USA
EditorIEEE Computer Society
Author(s)Rubén Heras Evangelio, Tobias Senst, Thomas Sikora
TitleDetection of Static Objects for the Task of Video Surveillance
AbstractDetecting static objects in video sequences has a high relevance in many surveillance scenarios like airports and railwaystations. In this paper we propose a system for the detection of static objects in crowded scenes that, based on the detection of two background models learning at different rates, classifies pixels with the help of a finite-state machine. The background is modelled by two mixtures of Gaussians with identical parameters except for the learning rate. The state machine provides the meaning for the interpretation of the results obtained from background subtraction and can be used to incorporate additional information cues, obtaining thus a flexible system specially suitable for real-life applications. The system was built in our surveillance application and successfully validated with several public datasets.
Key wordsVideo surveillance, abandoned objects