The goal of the MPLab is to develop systems that perceive and interact with humans in real time using natural communication channels. To this effect we are developing perceptual primitives to detect and track human faces and to recognize facial expressions. We are also developing algorithms for robots that develop and learn to interact with people on their own. Applications include personal robots, perceptive tutoring systems, and system for clinical assessment, monitoring, and intervention.

  • Introduction to the MPLab (PDF)
  • MPLAB 5 Year Progress Report (PDF)
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    NEWS


    Emot Aware Tutoring System http://bit.ly/7e6qX9

    From Harper’s Magazine “Yearly Review”, “Scientists [Tingfan Wu and Javier Movellan] in San Diego made a robot head study itself in a mirror until it learned to smile”

    ICDL: August 18-21 2010. University of Michingan. Ann Arbor. http://www.icdl-2010.org

    Head mounted cameras for polce officers: http://www.mercurynews.com/ci_14030412

    Hal Pashler Debunks evidence for learning styles. http://www.psychologicalscience.org/journals/index.cfm?journal=pspi&content=pspi/9_3

    NYT: Article on Studying young minds on how to teach them. http://www.nytimes.com/2009/12/21/health/research/21brain.html?_r=1&emc=eta1

    Robovie used as shopping companion http://www.youtube.com/watch?v=TneFT2hMKSY

    [Xiang et al.] Dynamic spatially smoothed regularization ensures boosting to select clustered but not scattered features.
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