Bilkent University
Department of Computer Engineering


Bilvideo-7: Video Parsing, Indexing and Retrieval


Muhammed Baştan
Ph.D Student
Computer Engineering Department
Bilkent University

Video indexing and retrieval aims to provide fast, natural and intuitive access to large video collections. This is getting more and more important as the amount of video data increases at a stunning rate. This thesis introduces the BilVideo-7 system to address the issues related to video parsing, indexing and retrieval.

BilVideo-7 is a distributed and MPEG-7 compatible video indexing and retrieval system that supports complex multimodal queries in a unified framework. The video data model is based on an MPEG-7 profile which is designed to represent the videos by decomposing them into Shots, Keyframes, Still Regions and Moving Regions. The MPEG-7 compatible XML representations of videos according to this profile are obtained by the MPEG-7 compatible video feature extraction and annotation tool of BilVideo-7, and stored in a native XML database. Users can formulate text, color, texture, shape, location, motion and spatiotemporal queries on an intuitive, easy-to-use visual query interface, whose composite query interface can be used to formulate very complex queries containing any type and number of video segments with their descriptors and specifying the spatio-temporal relations between them. The multi-threaded query processing server parses incoming queries into subqueries and executes each subquery in a separate thread. Then, it fuses subquery results in a bottom-up manner to obtain the final query result and sends the result to the originating client. The whole system is unique in that it provides very powerful querying capabilities with a wide range of descriptors and multimodal query processing in an MPEG-7 compatible interoperable environment.


DATE: 26 July, 2010, Monday @ 10:00