Name
Abstract | ||
|---|---|---|
This paper presents a discriminative temporal topic model (DTTM) for facial expression recognition. Our DTTM is developed by introducing temporal and categorical information into Latent Dirichlet Allocation (LDA) topic model. Temporal information is integrated by placing an asymmetric Dirichlet prior over document-topic distributions. The discriminative ability is improved by a supervised term weighting scheme. We describe the resulting DTTM in detail and show how it can be applied to facial expression recognition. Experiments on CMU expression database illustrate that the proposed DTTM is very effective in facial expression recognition. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-24028-7_55 | ISVC (1) |
Keywords | Field | DocType |
categorical information,asymmetric dirichlet,temporal information,cmu expression database,latent dirichlet allocation,topic model,discriminative ability,proposed dttm,facial expression recognition,discriminative temporal topic model | Latent Dirichlet allocation,Weighting,Pattern recognition,Categorical variable,Computer science,Speech recognition,Active appearance model,Facial expression,Artificial intelligence,Dirichlet distribution,Topic model,Discriminative model | Conference |
Citations | PageRank | References |
1 | 0.36 | 16 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lifeng Shang | 1 | 485 | 30.96 |
| Kwok Ping Chan | 2 | 313 | 23.52 |
| Guodong Pan | 3 | 1 | 1.38 |