An index and retrieval framework integrating perceptive features and semantics for multimedia databases

doi:10.1007/s11042-008-0235-y

	An index and retrieval framework integrating perceptive features and semantics for multimedia databases
	Shi, Zhiping; He, Qing; Shi, Zhongzhi
	2009-04-01
发表期刊	MULTIMEDIA TOOLS AND APPLICATIONS
ISSN	1380-7501
卷号	42 期号:2 页码:207-231
摘要	Typically, in multimedia databases, there exist two kinds of clues for query: perceptive features and semantic classes. In this paper, we propose a novel framework for multimedia databases index and retrieval integrating the perceptive features and semantic classes to improve the speed and the precision of the content-based multimedia retrieval (CBMR). We develop a semantics supervised clustering based index approach (briefly as SSCI): the entire data set is divided hierarchically into many clusters until the objects within a cluster are not only close in the perceptive feature space but also within the same semantic class, and then an index term is built for each cluster. Especially, the perceptive feature vectors in a cluster are organized adjacently in disk. So the SSCI-based nearest-neighbor (NN) search can be divided into two phases: first, the indexes of all clusters are scanned sequentially to get the candidate clusters with the smallest distances from the query example; second, the original feature vectors within the candidate clusters are visited to get search results. Furthermore, if the results are not satisfied, the SSCI supports an effective relevance feedback (RF) search: users mark the positive and negative samples regarded a cluster as unit instead of a single object; then the Bayesian classifiers on perceptive features and that on semantics are used respectively to adjust retrieval similarity distance. Our experiments show that SSCI-based searching was faster than VA(+)-based searching; the quality of the search result based on SSCI was better than that of the sequential search in terms of semantics; and a few cycles of the RF by the proposed approach can improve the retrieval precision significantly.
关键词	CBMR High-dimensional index Semantics Relevance feedback
DOI	10.1007/s11042-008-0235-y
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号	WOS:000263918300004
出版者	SPRINGER
引用统计	被引频次：4[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/11575
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Shi, Zhiping
作者单位	Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Shi, Zhiping,He, Qing,Shi, Zhongzhi. An index and retrieval framework integrating perceptive features and semantics for multimedia databases[J]. MULTIMEDIA TOOLS AND APPLICATIONS,2009,42(2):207-231.
APA	Shi, Zhiping,He, Qing,&Shi, Zhongzhi.(2009).An index and retrieval framework integrating perceptive features and semantics for multimedia databases.MULTIMEDIA TOOLS AND APPLICATIONS,42(2),207-231.
MLA	Shi, Zhiping,et al."An index and retrieval framework integrating perceptive features and semantics for multimedia databases".MULTIMEDIA TOOLS AND APPLICATIONS 42.2(2009):207-231.