Title :
Mixed ranking scheme for video retrieval
Author :
Feng, Y. ; Ren, Jinchang ; Jiang, Jianliang
Author_Institution :
Sch. of Inf., Univ. of Bradford, Bradford, UK
Abstract :
A unified ranking scheme for effective video retrieval is proposed, in which low-level visual feature terms and high-level image category features are combined organically to inspire effective retrieval in the manner of semantics. By taking these features as a joint fact of document relevance, the BM25 model, popular in text retrieval, is employed to determine a mixed similarity rank of video documents. Experiments using the well-known TRECVID retrieval dataset have validated the superiority of the methodology.
Keywords :
content-based retrieval; feature extraction; video retrieval; BM25 model; TRECVID retrieval dataset; document relevance; image category features; mixed ranking scheme; video document ranking; video retrieval; visual feature terms;
Journal_Title :
Electronics Letters
DOI :
10.1049/el.2010.8621