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This article is part of the series Advanced Video-Based Surveillance.

Open Access Open Badges Research Article

BigBackground-Based Illumination Compensation for Surveillance Video

MRyan Bales*, Dana Forsthoefel, Brian Valentine, DScott Wills and LindaM Wills

Author Affiliations

School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA

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EURASIP Journal on Image and Video Processing 2011, 2011:171363  doi:10.1155/2011/171363

The electronic version of this article is the complete one and can be found online at: http://jivp.eurasipjournals.com/content/2011/1/171363

Received:25 April 2010
Revisions received:26 October 2010
Accepted:13 December 2010
Published:21 December 2010

© 2011 M. Ryan Bales et al.

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.


Illumination changes cause challenging problems for video surveillance algorithms, as objects of interest become masked by changes in background appearance. It is desired for such algorithms to maintain a consistent perception of a scene regardless of illumination variation. This work introduces a concept we call BigBackground, which is a model for representing large, persistent scene features based on chromatic self-similarity. This model is found to comprise 50% to 90% of surveillance scenes. The large, stable regions represented by the model are used as reference points for performing illumination compensation. The presented compensation technique is demonstrated to decrease improper false-positive classification of background pixels by an average of 83% compared to the uncompensated case and by 25% to 43% compared to compensation techniques from the literature.

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