TY  - JOUR
PY  - 1999//
TI  - Modeling and prediction of human behavior
JO  - Neural computation
A1  - Liu, Aizhong
A1  - Pentland, A.
SP  - 229
EP  - 242
VL  - 11
IS  - 1
N2  - 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>
LA  - en
SN  - 0899-7667
UR  - http://dx.doi.org/
ID  - ref1
ER  -