MUSE: A Content-Based Image Search and Retrieval System Using Relevance Feedback
Multimedia Tools and Applications
Addressing the Problems of Bayesian Network Classification of Video Using High-Dimensional Features
IEEE Transactions on Knowledge and Data Engineering
Web Access to Large Audiovisual Assets Based on User Preferences
Multimedia Tools and Applications
Multimedia genre characterisation with fuzzy embedding classifiers
Proceedings of the 2008 Ambi-Sys workshop on Ambient media delivery and interactive television
Hi-index | 0.00 |
This paper presents an integrated framework for interactive content-based retrieval in video databases by means of visual queries. The proposed system incorporates algorithms for video shot detection, key-frame and shot selection, automated video object segmentation and tracking, and construction of multidimensional feature vectors using fuzzy classification of color, motion or texture segment properties. Retrieval is then performed in an interactive way by employing a parametric distance between feature vectors and updating distance parameters according to user requirements using relevance feedback. Experimental results demonstrate increased performance and flexibility according to user information needs.