Active background modeling: Actors on a stage

Raphael Sznitman, Henry Lin, Manaswi Gupta, Gregory Hager

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Over the last two decades, background modeling techniques have focused on representing the general appearance of a background that is assumed to be predominantly static. However, there are many situations in which there are active, moving elements that are effectively part of the background. Examples include tools in manipulative tasks or work settings where a small, fixed set of people are moving about. Such situations are not well modeled by traditional methods. In this paper, we present a background modeling approach, Actors on a Stage (AOS), that is able to accommodate both passive and active backgrounds. AOS is presented as a general, recursive estimation scheme for a background model. In this model, actors are a latent variable that is used to explain both occlusion of, and abrupt changes to, a background model. We demonstrate AOS in two different situations: a person writing on a blackboard, and a microretinal membrane peel. Additionally, we show how our method performs compared to traditional techniques in these settings, and on standard image sequences.

Original languageEnglish (US)
Title of host publication2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009
Pages1222-1228
Number of pages7
DOIs
StatePublished - 2009
Event2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009 - Kyoto, Japan
Duration: Sep 27 2009Oct 4 2009

Other

Other2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009
CountryJapan
CityKyoto
Period9/27/0910/4/09

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ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

Cite this

Sznitman, R., Lin, H., Gupta, M., & Hager, G. (2009). Active background modeling: Actors on a stage. In 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009 (pp. 1222-1228). [5457469] https://doi.org/10.1109/ICCVW.2009.5457469