Scene Categorization Using Topic Model Based Hierarchical Conditional Random Fields
By: gargvikram07- Scene Categorization Using Topic Model Based Hierarchical Conditional Random Fields
- Published on September 25, 2012
- gargvikram07
- Language - English
About this issue
We propose a novel hierarchical framework for scene categorization. The scene representation is defined by latent topics extracted by Latent Dirichlet Allocation. The interaction of these topics across scene categories is learned by probabilistic graphical modelling. We use Conditional Random Fields in a hierarchical setting for discovering the global context of these topics. The learned random fields are further used for categorization of a new scene. The experimental results of the proposed framework is presented on standard datasets and on image collection obtained from the internet.
About Scene Categorization Using Topic Model Based Hierarchical Conditional Random Fields
A statistical model to learn the context present in a general video via probabilistic graphical framework.