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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Dornaika, F. Raducanu, B. |
| Copyright Year | 2006 |
| Description | Author affiliation: Computer Vision Center, Spain (Dornaika, F.; Raducanu, B.) |
| Abstract | In this paper, we propose a novel approach for facial expression analysis and recognition. The proposed approach relies on tracked facial actions provided by an appearance-based 3D face tracker. For each universal expression, a dynamical model for facial actions given by an auto-regressive process is learned from training data. We classify a given image in an unseen video into one of the universal facial expression categories using an analysis-synthesis scheme. This scheme uses all models and select the one that provides the most consistent synthesized spatio-temporal facial actions. The dynamical models can be utilized in the tasks of synthesis and prediction. Experiments using unseen videos demonstrated the effectiveness of the developed method. |
| Starting Page | 8 |
| Ending Page | 8 |
| File Size | 415875 |
| Page Count | 1 |
| File Format | |
| ISBN | 0769526888 |
| DOI | 10.1109/AVSS.2006.96 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-11-22 |
| Publisher Place | Australia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Computer vision Head Image recognition Face recognition Hidden Markov models Psychology Pattern recognition Face detection Eyebrows Videos |
| Content Type | Text |
| Resource Type | Article |
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