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：2016
卷号：4
期号：4
页码：8018
DOI：10.15680/IJIRCCE.2016.0404351
出版社：S&S Publications
摘要：As the amount of information uploaded in internet is increasing day by day, in order to get the required information the huge database of information are needed to be analyzed properly. One of the widely used methods to analyze and retrieve these huge vide o data is video annotation. Video annotation process requires a large amount of processing to analyze the contents in the video as the process is complicated. This paper introduces a video annotation and retrieval system using SIFT and HOG features, in tha t SIFT given for training the classifiers. The SIFT and HOG features of the images are extracted and used for training the classifiers for doing a comparison on performance of the classifiers. An analysis of the results is done to find which feature is bet ter to train the classifier for getting more prominent annotated video database. Based on objects from the annotated video database, retrieval of the videos is also done
