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@InProceedings{ICRA08-lee,
	author="Juhyun Lee and Peter Stone",
	title="Person Tracking on a Mobile Robot with Heterogeneous Inter-Characteristic Feedback",
	booktitle= "{IEEE} International Conference on Robotics and Automation",
	location = "Pasadena, CA",
	month = "May",
	year="2008",
	abstract="For a mobile robot that interacts with humans such as a home assistant
		or a tour guide robot, tracking a particular person among multiple
		persons is a fundamental, yet challenging task.  Uniquely identifying
		characteristics such as a person's face, may not be visible consistently
		enough to be used as the sole form of identification.  Rather, it may be
		useful to also track more frequently visible, but perhaps less uniquely
		identifying characteristics such as a person's clothes.  After learning
		various characteristics of a person, the tracking system is required to
		autonomously update itself with additional training data, since the
		learned features may change over space and time due to the mobile
		nature of the robot.  In this paper, we introduce a novel algorithm for
		merging multiple, heterogeneous sub-classifiers designed to track and
		associate different characteristics of a person being tracked.  These
		heterogeneous classifiers give feedback to each other by identifying
		additional online training data for one another, thus improving the
		performance of each classifier and the accuracy of the overall system. 
		Our algorithm has been fully implemented and tested on a Segway base.",
	wwwnote={<a href="http://www.icra2008.org/">ICRA 2008</a>},
 }