Sequential Bayesian Nonparametric Multimodal Topic Models for Video Data Analysis

Jianfei XUE, Koji EGUCHI
2018 IEICE transactions on information and systems  
Topic modeling as a well-known method is widely applied for not only text data mining but also multimedia data analysis such as video data analysis. However, existing models cannot adequately handle time dependency and multimodal data modeling for video data that generally contain image information and speech information. In this paper, we therefore propose a novel topic model, sequential symmetric correspondence hierarchical Dirichlet processes (Seq-Sym-cHDP) extended from sequential
more » ... lly independent hierarchical Dirichlet processes (Seq-CI-HDP) and sequential correspondence hierarchical Dirichlet processes (Seq-cHDP), to improve the multimodal data modeling mechanism via controlling the pivot assignments with a latent variable. An inference scheme for Seq-Sym-cHDP based on a posterior representation sampler is also developed in this work. We finally demonstrate that our model outperforms other baseline models via experiments. key words: bayesian nonparametric methods, multimedia data mining, hierarchical Dirichlet processes, topic models Jianfei Xue is currently pursuing a Ph.D
doi:10.1587/transinf.2017dap0021 fatcat:oukkqsre2ncddgu6v6son5yh3i