NDLI: Kalman filter based video background estimation

Content Provider	IEEE Xplore Digital Library
Author	Scott, J. Pusateri, M.A. Cornish, D.
Copyright Year	2009
Description	Author affiliation: Electrical and Computer Engineer Digital Imaging Group, heatfusion 10416 Theodore Green Boulevard, White Plains, Maryland 20695 (Scott, J.) \|\| Multidimensional Image Processing Lab, Penn State University, 304 Electrical Engineering West, University Park, Pennsylvania 16802 (Cornish, D.) \|\| Integrated Design Services, Penn State University, 149 Hammond Building, University Park, Pennsylvania 16802 (Pusateri, M.A.)
Abstract	Transferring responsibility for object tracking in a video scene to computer vision rather than human operators has the appeal that the computer will remain vigilant under all circumstances while operator attention can wane. However, when operating at their peak performance, human operators often outperform computer vision because of their ability to adapt to changes in the scene. While many tracking algorithms are available, background subtraction, where a background image is subtracted from the current frame to isolate the foreground objects in a scene, remains a well proven and popular technique. Under some circumstances, a background image can be obtained manually when no foreground objects are present. In the case of persistent surveillance outdoors, the background has a time evolution due to diurnal changes, weather, and seasonal changes. Such changes render a fixed background scene inadequate. We present a method for estimating the background of a scene utilizing a Kalman filter approach. Our method applies a one-dimensional Kalman filter to each pixel of the camera array to track the pixel intensity. We designed the algorithm to track the background intensity of a scene assuming that the camera view is relatively stationary and that the time evolution of the background occurs much slower than the time evolution of relevant foreground events. This allows the background subtraction algorithm to adapt automatically to changes in the scene. The algorithm is a two step process of mean intensity update and standard deviation update. These updates are derived from standard Kalman filter equations. Our algorithm also allows objects to transition between the background and foreground as appropriate by modeling the input standard deviation. For example, a car entering a parking lot surveillance camera field of view would initially be included in the foreground. However, once parked, it will eventually transition to the background. We present results validating our algorithm's ability to estimate backgrounds in a variety of scenes. We demonstrate the application of our method to track objects using simple frame detection with no temporal coherency.
Starting Page	1
Ending Page	7
File Size	1021564
Page Count	7
File Format	PDF
ISBN	9781424451463
ISSN	15505219
DOI	10.1109/AIPR.2009.5466306
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Layout Surveillance Computer vision Cameras Design engineering Humans Equations Object detection Delay State estimation
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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