Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Static Object Detection Based on a Dual Background Model and a Finite-State Machine Rub´ n Heras Evangelio and Thomas Sikora e | Hindawi Publishing Corporation EURASIP Journal on Image and Video Processing Volume 2011 Article ID 858502 11 pages doi 2011 858502 Research Article Static Object Detection Based on a Dual Background Model and a Finite-State Machine Ruben Heras Evangelio and Thomas Sikora Communication Systems Group Technical University of Berlin D-10587 Berlin Germany Correspondence should be addressed to Ruben Heras Evangelio heras@ Received 30 April 2010 Revised 11 October 2010 Accepted 13 December 2010 Academic Editor Luigi Di Stefano Copyright 2011 R. Heras Evangelio and T. Sikora. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 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 lookup 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. 1. Introduction Detecting static objects in video sequences has several applications in surveillance systems such as the detection of illegally parked vehicles in traffic monitoring or the detection of .
