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.
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References
Blei, D., Ng, A., Jordan, M.: Latent dirichlet allocation. JMLR 3(2-3), 993–1022 (2003)
Blei, D., Lafferty, J.D.: Dynamic topic models. In: ICML (2006)
Blei, D., McAuliffe, J.D.: Supervised topic models. In: NIPS, pp. 121–128 (2007)
Chang, Y., Hu, C., Turk, M.: Probabilistic expression analysis on manifolds. In: CVPR, pp. 520–527 (2004)
Cootes, T.F., Edwards, G.J., Taylor, C.J.: Active appearance models. IEEE Trans. on PAMI 23(6), 681–685 (2001)
Debole, F. and Sebastiani, F.: Supervised term weighting for automated text categorization. In: ACM SAC, pp. 784–788 (2003)
Ekman, P., Friesen, W.V.: Facial Action Coding System (FACS): Manual. Consulting Psychologists Press, Palo Alto (1978)
Fei-Fei, L., Perona, P.: A bayesian hierarchical model for learning natural scene categories. In: CVPR, pp. 524–531 (2005)
Griffiths, T.L., Steyvers, M.: Finding scientific topics. PNAS 101, 5228–5235 (2004)
Kanade, T., Cohn, J.F., Tian, Y.: Comprehensive database for facial expression analysis. In: FG, pp. 46–53 (2000)
Lacoste-Julien, S., Sha, F., Jordan, M.I.: DiscLDA: Discriminative learning for dimensionality reduction and classification. In: NIPS, pp. 897–904 (2008)
Shang, L., Chan, K.P.: A temporal latent topic model for facial expression recognition. In: Kimmel, R., Klette, R., Sugimoto, A. (eds.) ACCV 2010, Part IV. LNCS, vol. 6495, pp. 51–63. Springer, Heidelberg (2011)
Steyvers, M., Smyth, P., Rosen-Zvi, M., Griffiths, T.: Probabilistic Author-Topic Models for Information Discovery. In: KDD, pp. 306–315 (2004)
Wang, X., Grimson, E.: Spatial latent dirichlet allocation. In: NIPS (2007)
Wang, C., Blei, D., Heckerman, D.: Continuous time dynamic topic models. In: UAI (2008)
Wang, X., McCallum, A.: Topics over time: A non-Markov continuous-time model of topical trends. In: SIGKDD (2006)
Wei, X., Sun, J., Wang, X.: Dynamic mixture models for multiple time-series. In: IJCAI, pp. 2909–2914 (2007)
Wilson, A.T., Chew, P.A.: Term weighting schmes for latent Dirichlet allocation. In: NAACL, pp. 465–473 (2010)
Zhou, M., Liang, L., Sun, J., Wang, Y.: AAM based face tracking with temporal matching and face segmentation. In: CVPR, pp. 701-708 (2010)
Zhu, J., Ahmed, A., Xing, E.P.: MedLDA: Maximum margin supervised topic models for regression and classification. In: ICML (2009)
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Shang, L., Chan, KP., Pan, G. (2011). DTTM: A Discriminative Temporal Topic Model for Facial Expression Recognition. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2011. Lecture Notes in Computer Science, vol 6938. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24028-7_55
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DOI: https://doi.org/10.1007/978-3-642-24028-7_55
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