@article{ref1,
title="Modeling and prediction of human behavior",
journal="Neural computation",
year="1999",
author="Liu, Aizhong and Pentland, A.",
volume="11",
number="1",
pages="229-242",
abstract="We propose that many human behaviors can be accurately described as a set of dynamic modes (e.g., Kalman filters) sequenced together by a Markov chain. We then use these dynamic Markov models to recognize human behaviors from sensory data and to predict human behaviors over a few seconds time. To test the power of this modeling approach, we report an experiment in which we were able to achieve 95% accuracy at predicting automobile drivers' subsequent actions from their initial preparatory movements.<p /> <p>Language: en</p>",
language="en",
issn="0899-7667",
doi="",
url="http://dx.doi.org/"
}