Institute of Computing Technology, Chinese Academy IR
Semantics supervised cluster-based index for video databases | |
Shi, Zhiping; Li, Qingyong; Shil, Zhiwei; Shil, Zhongzhi | |
2006 | |
发表期刊 | IMAGE AND VIDEO RETRIEVAL, PROCEEDINGS |
ISSN | 0302-9743 |
卷号 | 4071页码:453-462 |
摘要 | High-dimensional index is one of the most challenging tasks for content-based video retrieval (CBVR). Typically, in video database, there exist two kinds of clues for query: visual features and semantic classes. In this paper, we modeled the relationship between semantic classes and visual feature distributions of data set with the Gaussian mixture model (GMM), and proposed a semantics supervised cluster based index approach (briefly as SSCI) to integrate the advantages of both semantic classes and visual features. The entire data set is divided hierarchically by a modified clustering technique into many clusters until the objects within a cluster are not only close in the visual feature space but also within the same semantic class, and then an index entry including semantic clue and visual feature clue is built for each cluster. Especially, the visual feature vectors in a cluster are organized adjacently in disk. So the SSCI-based nearest-neighbor (NN) search can be divided into two phases: the first phase computes the distances between the query example and each cluster index and returns the clusters with the smallest distance, here namely candidate clusters; then the second phase retrieves the original feature vectors within the candidate clusters to gain the approximate nearest neighbors. Our experiments showed that for approximate searching the SSCI-based approach was faster than VA(+)-based approach; moreover, the quality of the result set was better than that of the sequential search in terms of semantics. |
关键词 | high-dimensional index cluster video semantics video database |
收录类别 | SCI |
语种 | 英语 |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence ; Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods |
WOS记录号 | WOS:000239566500046 |
出版者 | SPRINGER-VERLAG BERLIN |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.204/handle/2XEOYT63/10682 |
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 | 1.Chinese Acad Sci, Inst Comp Technol, Beijing 100080, Peoples R China 2.Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, Peoples R China |
推荐引用方式 GB/T 7714 | Shi, Zhiping,Li, Qingyong,Shil, Zhiwei,et al. Semantics supervised cluster-based index for video databases[J]. IMAGE AND VIDEO RETRIEVAL, PROCEEDINGS,2006,4071:453-462. |
APA | Shi, Zhiping,Li, Qingyong,Shil, Zhiwei,&Shil, Zhongzhi.(2006).Semantics supervised cluster-based index for video databases.IMAGE AND VIDEO RETRIEVAL, PROCEEDINGS,4071,453-462. |
MLA | Shi, Zhiping,et al."Semantics supervised cluster-based index for video databases".IMAGE AND VIDEO RETRIEVAL, PROCEEDINGS 4071(2006):453-462. |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论