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Local Eigen Background Substraction

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Image Processing and Communications Challenges 5

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 233))

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Summary

The article describes the extended background modeling based on the well-known Eigenbackground method. The idea presented in the article expands the Eigenbackground method, breaking the scene into many smaller ones, modeling the background separately for each of its sections. This approach allows for better separation of the foreground objects, and better modeling of spots in which the light changes. Furthermore, it also ensures efficient implementation of the algorithm for CUDA graphics cards, separating particular local models into threads. In the future the approach shall also enable users to update models more efficiently when locally there occurs no movement in a given section.

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References

  1. Oliver, N.M., Rosario, B., Pentland, A.P.: A Bayesian computer vision system for modeling human interactions. IEEE Transactions (2000)

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  2. Gritti, T.: Robust Background Subtraction with Incremental Eigen Models. Philips Research (2008)

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  3. Parks, D.H., Fels, S.S.: Evaluation of Background Subtraction Algorithms with Post-Processing. In: IEEE Fifth International Conference on Advanced Video and Signal Based Surveillance, AVSS 2008 (2008)

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  4. Renno, J., Greenhill, D., Orwell, J., Jones, G.A.: Adaptive eigenbackgrounds for object detection. In: 2004 International Conference on Image Processing, ICIP 2004 (2004)

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Correspondence to Paweł Ziubiński .

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© 2014 Springer International Publishing Switzerland

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Ziubiński, P., Garbat, P., Zawistowski, J. (2014). Local Eigen Background Substraction. In: S. Choras, R. (eds) Image Processing and Communications Challenges 5. Advances in Intelligent Systems and Computing, vol 233. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-01622-1_24

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  • DOI: https://doi.org/10.1007/978-3-319-01622-1_24

  • Publisher Name: Springer, Heidelberg

  • Print ISBN: 978-3-319-01621-4

  • Online ISBN: 978-3-319-01622-1

  • eBook Packages: EngineeringEngineering (R0)

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