Video Data Visualization System: Semantic Classification And   Personalization
  We present in this paper an intelligent video data visualization tool, based on semantic classification, for retrieving and exploring a large scale corpus of videos. Our work is based on semantic classification resulting from semantic analysis of video. The obtained classes will be projected in the visualization space. The graph is represented by nodes and edges, the nodes are the keyframes of video documents and the edges are the relation between documents and the classes of documents. Finally, we construct the user's profile, based on the interaction with the system, to render the system more adequate to its references. 
Jamel Slimi, Anis Ben Ammar and Adel M. Alimi
cs.IR cs.CV cs.MM