Static Object Detection Based on a Dual Background Model and a Finite-State Machine. (26th December 2010)

• Record Type: Journal Article
• Authors: Heras Evangelio Heras Evangelio, Rubén Rubén; Sikora Sikora, Thomas Thomas
• Other Names: Di Stefano Di Stefano Luigi Luigi Academic Editor.
• Is Part Of: EURASIP journal on image and video processing. Volume 2011(2011)
• Publication Date: 2010-12-26
• Subjects: Image processing -- Digital techniques -- Periodicals; Digital video -- Periodicals; Traitement d'images; Vidéo numérique; Digital video; Image processing -- Digital techniques; Periodicals; Electronic journal; Electronic journals; 621.367
• DOI: 10.1155/2011/858502
• Languages: English
• ISSNs: 1687-5176

Abstract

Abstract : Detecting static objects in video sequences has a high relevance in many surveillance applications, such as the detection of abandoned objects in public areas. In this paper, we present a system for the detection of static objects in crowded scenes. Based on the detection of two background models learning at different rates, pixels are classified 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; it can be implemented as a look-up table with negligible computational cost and it can be easily extended. Due to the definition of the states in the state machine, the system can be used either full automatically or interactively, making it extremely suitable for real-life surveillance applications. The system was successfully validated with several public datasets.