Hierarchical unsupervised learning of facial expression categories
- 13 November 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
We consider the problem of unsupervised classification of temporal sequences of facial expressions in video. This problem arises in the design of an adaptive visual agent, which must be capable of identifying appropriate classes of visual events without supervision to effectively complete its tasks. We present a multilevel dynamic Bayesian network that learns the high-level dynamics of facial expressions simultaneously, with models of the expressions themselves. We show how the parameters of the model can be learned in a scalable and efficient way. We present preliminary results using real video data and a class of simulated dynamic event models. The results show that our model correctly classifies the input data comparably to a standard event classification approach, while also learning the high-level model parameters.Keywords
This publication has 10 references indexed in Scilit:
- Learning structured behaviour models using variable length Markov modelsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Action recognition using probabilistic parsingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- ASL recognition based on a coupling between HMMs and 3D motion analysisPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Understanding purposeful human motionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Representation and recognition of complex human motionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Segmenting visual actions based on spatio-temporal motion patternsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Recognizing action units for facial expression analysisPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2001
- Recognizing Facial Expressions in Image Sequences Using Local Parameterized Models of Image MotionInternational Journal of Computer Vision, 1997
- Eigenfaces for RecognitionJournal of Cognitive Neuroscience, 1991
- A Step Towards Unification of Syntactic and Statistical Pattern RecognitionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1986