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Efficient video retrieval using index structure
Author(s) -
Zhang Jing
Publication year - 2008
Publication title -
international journal of imaging systems and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.359
H-Index - 47
eISSN - 1098-1098
pISSN - 0899-9457
DOI - 10.1002/ima.20154
Subject(s) - computer science , video retrieval , similarity measure , video tracking , similarity (geometry) , sliding window protocol , index (typography) , information retrieval , artificial intelligence , construct (python library) , video post processing , window (computing) , frame (networking) , video compression picture types , video processing , computer vision , image (mathematics) , world wide web , telecommunications , programming language , operating system
Video retrieval remains a challenging problem since most of traditional query algorithms are ineffectual and time‐consuming. In this article, we proposed a new video retrieval method, which segments the video stream by visual similarity between neighboring frames, and adopt the high‐dimensional index structure to organize segments. Furthermore, a new similarity measure is brought forward to improve the query accuracy by synthetically taking into account the visual similarity and temporal order among video segments. Based on the similarity measure, we propose a novel video clip retrieval algorithm which achieves high query efficiency by using restricted sliding window to construct candidate video clips. Experimental results show that the proposed video retrieval method is efficient and effective. © 2008 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 18, 113–123, 2008