Latent Dirichlet Allocation Mixture Model
(Redirected from LDA Mixture Model)
Jump to navigation
Jump to search
A Latent Dirichlet Allocation Mixture Model is a mixture model based on Latent Dirichlet Allocation.
References
2009
- (Wang et al., 2009) ⇒ Xiaogang Wang, Xiaoxu Ma, and W. E. L. Grimson. (2009). “Unsupervised Activity Perception in Crowded and Complicated Scenes Using Hierarchical Bayesian Models.” In: IEEE Transactions on Pattern Analysis and Machine Intelligence Journal, 31(3). doi:10.1109/TPAMI.2008.87
- QUOTE: We propose a novel unsupervised learning framework to model activities and interactions in crowded and complicated scenes. Hierarchical Bayesian models are used to connect three elements in visual surveillance: low-level visual features, simple "atomic" activities, and interactions. … In this paper, we propose three hierarchical Bayesian models, Latent Dirichlet Allocation (LDA) mixture model, Hierarchical Dirichlet Process (HDP) mixture model, and Dual Hierarchical Dirichlet Processes (Dual-HDP) model.