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Multilayer background modeling under occlusions

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Abstract

A multilayer background modeling technique is presented for video surveillance. Rather than simply classifying all features in a scene as either dynamically moving foreground or long-lasting, stationary background, a temporal model is used to place each scene object in time relative to each other. Foreground objects that become stationary are registered as layers on top of the background layer. In this process of layer formation, the algorithm deals with ”fake objects” created by moved background, and noise created by dynamic background and moving foreground objects. Objects that leave the scene are removed based on the occlusion reasoning among layers. The technique allows us to understand and visualize a scene with multiple objects entering, leaving, and occluding each other at different points in time. This scene understanding leads to a richer representation of temporal scene events than traditional foreground/background segmentation. The technique builds on a low-cost background modeling technique that makes it suitable for embedded, real-time platforms.

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Authors and Affiliations

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

    Shoaib Azmat, Linda Wills & Scott Wills

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  1. Shoaib Azmat
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  2. Linda Wills
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  3. Scott Wills
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Correspondence to Shoaib Azmat.

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Azmat, S., Wills, L. & Wills, S. Multilayer background modeling under occlusions. Machine Vision and Applications 25, 1399–1409 (2014). https://doi.org/10.1007/s00138-014-0614-5

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  • DOI: https://doi.org/10.1007/s00138-014-0614-5

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