期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2014
卷号：2
期号：5
出版社：S&S Publications
摘要：It is commonly acknowledged that ever-increasing video databases should be efficiently indexed tofacilitate fast video retrieval. Categorizing web-based videos is an important yet challenging task. The difficulties arisefrom large data diversity within a category, lack of labelled data etc. Similarity matching algorithm plays an importantrole in Video Retrieval System. Most of the video retrieval systems are designed using traditional similarity matchingalgorithms that are based on distance measures. The Accuracy of retrieval system depends on the method used fordetecting shots, kind of video features used for retrieval. Semantic video indexing is a step towards automatic videoindexing and retrieval. Here a Latent semantic indexing (LSI) technique, based on Singular Value Decomposition andfusion of visual features like color and edge is proposed for video indexing and retrieval. A key feature of LSI is itsability to establish associations between similar kinds of information, so the probability of producing accurate index isvery high.
关键词：Latent Semantic Indexing; Singular Value Decomposition; Video Visual Feature; Similarity Matching;Algorithm; Video Retrieval System.
