Stationary foreground detection using background subtraction and temporal difference in video surveillance
EntityUAM. Departamento de Tecnología Electrónica y de las Comunicaciones
PublisherInstitute of Electrical and Electronics Engineers
10.1109/ICIP.2010.565069917th IEEE International Conference on Image Processing, ICIP 2010. IEEE, 2010. 4657-4660
ISBN978-1-4244-7993-1 (online); 978-1-4244-7992-4 (print)
Funded byWork supported by the Spanish Government (TEC2007- 65400 SemanticVideo), by Cátedra Infoglobal-UAM for “Nuevas Tecnologías de video aplicadas a la seguridad”, by the Consejería de Educación of the Comunidad de Madrid and by the European Social Fund.
SubjectsBackground subtraction; Frame difference; Stationary foreground detection; Video surveillance; Telecomunicaciones
NotePersonal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Á. Bayona, J. C. SanMiguel, and Martínez, "Stationary foreground detection using background subtraction and temporal difference in video surveillance", in 17th IEEE International Conference on Image Processing, ICIP 2010, p. 4657 - 4660
Rights© 2010 IEEE
In this paper we describe a new algorithm focused on obtaining stationary foreground regions, which is useful for applications like the detection of abandoned/stolen objects and parked vehicles. Firstly, a sub-sampling scheme based on background subtraction techniques is implemented to obtain stationary foreground regions. Secondly, some modifications are introduced on this base algorithm with the purpose of reducing the amount of stationary foreground detected. Finally, we evaluate the proposed algorithm and compare results with the base algorithm using video surveillance sequences from PETS 2006, PETS 2007 and I-LIDS for AVSS 2007 datasets. Experimental results show that the proposed algorithm increases the detection of stationary foreground regions as compared to the base algorithm.
This item appears in the following Collection(s)
Showing items related by title, author, creator and subject.