Content-Based Video Indexing and Retrieval
Jianping Fan (University of North Carolina-Charlotte, USA), Xingquan Zhu (Purdue University, USA) and Jing Xiao (University of North Carolina–Charlotte, USA)
Copyright: © 2004
Recent advances in digital video compression and networks have made videos more accessible than ever. Several content-based video retrieval systems have been proposed in the past. In this chapter, we first review these existing content-based video retrieval systems and then propose a new framework, called ClassView, to make some advances towards more efficient content-based video retrieval. This framework includes: (a) an efficient video content analysis and representation scheme to support high-level visual concept characterization; (b) a hierarchical video classification technique to bridge the semantic gap between low-level visual features and high-level semantic visual concepts; and (c) a hierarchical video database indexing structure to enable video access over large-scale database. Integrating video access with efficient database indexing tree structures has provided a great opportunity for supporting more powerful video search engines.