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@InProceedings(AAAI05-vision,
        author="Mohan Sridharan and Peter Stone",
        title="Autonomous Color Learning on a Mobile Robot",
        booktitle="Proceedings of the Twentieth National Conference on Artificial Intelligence",
        month="July",year="2005",
        abstract={
                  Color segmentation is a challenging subtask in
                  computer vision. Most popular approaches are
                  computationally expensive, involve an extensive
                  off-line training phase and/or rely on a stationary
                  camera.  This paper presents an approach for color
                  learning on-board a legged robot with limited
                  computational and memory resources. A key defining
                  feature of the approach is that it works without any
                  labeled training data.  Rather, it trains
                  autonomously from a color-coded model of its
                  environment.  The process is fully implemented,
                  completely autonomous, and provides high degree of
                  segmentation accuracy.
                 },
        wwwnote={Some <a href="http://www.cs.utexas.edu/users/AustinVilla/?p=research/auto_vis">videos of the robot</a> referenced in the paper.<br>
<a href="http://www.aaai.org/Conferences/National/2005/aaai05.html">AAAI 2005</a>},
)