Abstract
We present a novel approach for supervised domain adaptation that is based upon the probabilistic framework of Gaussian processes (GPs). Specifically, we introduce domain-specific GPs as local experts for facial expression classification from face images. The adaptation of the classifier is facilitated in probabilistic fashion by conditioning the target expert on multiple source experts. Furthermore, in contrast to existing adaptation approaches, we also learn a target expert from available target data solely. Then, a single and confident classifier is obtained by combining the predictions from multiple experts based on their confidence. Learning of the model is efficient and requires no retraining/reweighting of the source classifiers. We evaluate the proposed approach on two publicly available datasets for multi-class (MultiPIE) and multi-label (DISFA) facial expression classification. To this end, we perform adaptation of two contextual factors: 'where' (view) and 'who' (subject). We show in our experiments that the proposed approach consistently outperforms both source and target classifiers, while using as few as 30 target examples. It also outperforms the state-of-the-art approaches for supervised domain adaptation.
Original language | English |
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Title of host publication | 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW 2016) |
Subtitle of host publication | Las Vegas, Nevada, USA, 26 June - 1 July 2016 |
Place of Publication | Piscataway, NJ |
Publisher | IEEE Computer Society |
Pages | 1469-1477 |
Number of pages | 9 |
ISBN (Electronic) | 978-1-5090-1438-5 |
ISBN (Print) | 978-1-5090-1437-8 |
DOIs | |
Publication status | Published - Jun 2016 |
Event | 29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016 - Las Vegas, NV, USA, Las Vegas, United States Duration: 26 Jun 2016 → 1 Jul 2016 Conference number: 29 |
Publication series
Name | IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) |
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Publisher | IEEE Computer Society |
ISSN (Print) | 2160-7516 |
Conference
Conference | 29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016 |
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Abbreviated title | CVPR 2016 |
Country | United States |
City | Las Vegas |
Period | 26/06/16 → 1/07/16 |
Other | 29 June - 1 July 2016 |
Keywords
- HMI-HF: Human Factors
- facial behavior analysis
- IR-103096
- Gaussian processes
- METIS-320877
- EWI-27133