Ontology Based Video Annotation and Retrieval System

As the multimedia content over the internet is increasing day by day, efficient methods for retrieval of these huge amount of data is required. Video annotation is one of the widely used methods to analyze and retrieve these huge video data. The process of video annotation is complicated as it requires a large amount of processing to analyze the contents in the video. This paper introduces a video annotation system based on ontology with HoG features 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 better to train the classifier for getting more prominent annotated video database. Retrieval of the videos based on objects from the annotated video database is also done. KeywordsKey frame extraction, Feature extraction,