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The JAMF Attention Modelling Framework

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5395))

Abstract

Many models of attention have been implemented in recent years, but comparison and further development are difficult due to the lack of a common platform. We present JAMF, an open source simulation framework for drag & drop design and high-performance execution of attention models. Its building blocks are “Components”, functional units encapsulating specific algorithms. Simulations are created in the graphical JAMF client by connecting Components from the server’s repository. Today it contains Components suitable for replication and extension of many major models of attention. Simulations are executed on the JAMF server by translation of model definitions into binary applications, while automatically exploiting the model’s structure for parallel execution. By disentangling design and algorithmic implementation, the JAMF architecture combines a novel tool for rapid test and implementation of attention models with a high-performance execution engine.

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References

  1. Schumann, F., Acik, A., Onat, S., König, P.: Integration of different features in guiding eye-movements. In: Proceedings of the 7th Meeting of the German Neuroscience Society / 31th Göttingen Neurobiology Conference, Neuroforum 2007, Göttingen, Germany (2007)

    Google Scholar 

  2. Tsotsos, J., Culhane, S., Kei Wai, W., Lai, Y., Davis, N., Nuflo, F.: Modeling visual attention via selective tuning. Artificial Intelligence 78(1-2), 507–545 (1995)

    Article  Google Scholar 

  3. Kienzle, W., Wichmann, F., Scholkopf, B., Franz, M.: Learning an Interest Operator from Human Eye Movements. In: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

    Google Scholar 

  4. Itti, L., Koch, C., Niebur, E., et al.: A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 20(11), 1254–1259 (1998)

    Article  Google Scholar 

  5. Itti, L.: The ilab neuromorphic vision C++ toolkit: Free tools for the next generation of vision algorithms (2004)

    Google Scholar 

  6. Itti, L., Baldi, P.: A principled approach to detecting surprising events in video. In: Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), San Diego, CA, pp. 631–637 (June 2005)

    Google Scholar 

  7. Johnson, G., Jennings, R.: LabVIEW Graphical Programming. McGraw-Hill Professional, New York (2001)

    Google Scholar 

  8. Rothenstein, A., Zaharescu, A., Tsotsos, J.: TarzaNN: A general purpose neural network simulator for visual attention modeling. In: Paletta, L., Tsotsos, J.K., Rome, E., Humphreys, G.W. (eds.) WAPCV 2004. LNCS, vol. 3368, pp. 159–167. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

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© 2009 Springer-Verlag Berlin Heidelberg

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Steger, J., Wilming, N., Wolfsteller, F., Höning, N., König, P. (2009). The JAMF Attention Modelling Framework. In: Paletta, L., Tsotsos, J.K. (eds) Attention in Cognitive Systems. WAPCV 2008. Lecture Notes in Computer Science(), vol 5395. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00582-4_12

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  • DOI: https://doi.org/10.1007/978-3-642-00582-4_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-00581-7

  • Online ISBN: 978-3-642-00582-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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