University of Oxford video retrieval system

ABSTRACT

Fast multimedia retrieval in large video datasets remains an extremely challenging problem. This system explores how novel techniques from Computer Vision can be used to search in cases where the subtitle text is uninformative (e.g. actions, particular objects).

REFERENCES

• 1: J. Philbin, A. Bosch, O. Chum, J. Geusebroek, J. Sivic, and A. Zisserman. Oxford trecvid 2006 - notebook paper. In Proceedings of the TRECVID 2006 Workshop, Nov. 2006.
• 2: J. Philbin, O. Chum, M. Isard, J. Sivic, and A. Zisserman. Object retrieval with large vocabularies and fast spatial matching. 2007.
• 3: Josef Sivic , Andrew Zisserman, Video Google: A Text Retrieval Approach to Object Matching in Videos, Proceedings of the Ninth IEEE International Conference on Computer Vision, p.1470, October 13-16, 2003

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.1 Content Analysis and Indexing
          Subjects: Indexing methods

General Terms:
Algorithms

Keywords:
computer vision, retrieval