Skip Navigation
York U: Redefine the PossibleHOME | Current Students | Faculty & Staff | Research | International
Search »FacultiesLibrariesCampus MapsYork U OrganizationDirectorySite Index
Future Students, Alumni & Visitors
2016 Technical Reports

Background Image Modelling for Change Detection

Hang Gao and Richard P. Wildes

Technical Report EECS-2016-01

York University

January 7 2016


Change detection relative to a background image model is a potentially enabling capability for a variety of image analysis tasks, including automated video surveillance and monitoring. In this report, various combinations of chromatic, spatial and dynamic features are proposed and evaluated with reference to background modelling for change detection. The features are embedded in a popular background modelling framework and empirically evaluated relative to each other as well as the state-of-the-art on a standared, publicly available change detection dataset.

Download paper in PDF format.

The documents distributed by this server have been provided by the contributing authors as a means to ensure timely dissemination of scholarly and technical work on a noncommercial basis. Copyright and all rights therein are maintained by the authors or by other copyright holders, notwithstanding that they have offered their works here electronically. It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.