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Preliminary Implementation of Context-Aware Attention System for Humanoid Robots

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Biomimetic and Biohybrid Systems (Living Machines 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8064))

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Abstract

A context-aware attention system is fundamental for regulating the robot behaviour in a social interaction since it enables social robots to actively select the right environmental stimuli at the right time during a multiparty social interaction. This contribution presents a modular context-aware attention system which drives the robot gaze. It is composed by two modules: the scene analyzer module manages incoming data flow and provides a human-like understanding of the information coming from the surrounding environment; the attention module allows the robot to select the most important target in the perceived scene on the base of a computational model. After describing the motivation, we report the proposed system and the preliminary test.

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References

  1. Begum, M., Karray, F.: Visual attention for robotic cognition: a survey. IEEE Transactions on Autonomous Mental Development 3(1), 92–105 (2011)

    Article  Google Scholar 

  2. Mazzei, D., Lazzeri, N., Hanson, D., De Rossi, D.: Hefes: An hybrid engine for facial expressions synthesis to control human-like androids and avatars. In: 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), pp. 195–200. IEEE (2012)

    Google Scholar 

  3. Butko, N.J., Zhang, L., Cottrell, G.W., Movellan, J.R.: Visual saliency model for robot cameras. In: International Conference in Robotics and Automation, pp. 2398–2403. IEEE (2008)

    Google Scholar 

  4. Itti, L., Dhavale, N., Pighin, F.: Realistic avatar eye and head animation using a neurobiological model of visual attention. In: SPIE’s 48th Annual Meeting, International Society for Optics and Photonics, pp. 64–78 (2004)

    Google Scholar 

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© 2013 Springer-Verlag Berlin Heidelberg

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Zaraki, A., Mazzei, D., Lazzeri, N., Pieroni, M., De Rossi, D. (2013). Preliminary Implementation of Context-Aware Attention System for Humanoid Robots. In: Lepora, N.F., Mura, A., Krapp, H.G., Verschure, P.F.M.J., Prescott, T.J. (eds) Biomimetic and Biohybrid Systems. Living Machines 2013. Lecture Notes in Computer Science(), vol 8064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39802-5_65

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  • DOI: https://doi.org/10.1007/978-3-642-39802-5_65

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39801-8

  • Online ISBN: 978-3-642-39802-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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