Driver monitoring for a human-centered driver assistance system
Proceedings of the 1st ACM international workshop on Human-centered multimedia
Simultaneous eye tracking and blink detection with interactive particle filters
EURASIP Journal on Advances in Signal Processing
Compatible particles for part-based tracking
AMDO'10 Proceedings of the 6th international conference on Articulated motion and deformable objects
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In this paper we present a framework for tracking nonrigid facial landmarks by combining various visual cues at multiple levels of detail. Using a probabilistic framework consisting of a hierarchy of particle filters, we are able to track individual facial landmarks using multiple visual cues at the local level, as well as tracking results at more coarse level of detail. This allows for the fusion of global and local cues in an efficient and robust manner. Testing is performed by tracking and classifying facial action codes obtained from the Cohn-Kanade AU-Coded Facial Expression Database.