| This work aims to provide a semantic web based framework for content-based video retrieval. Currently, we do not have scalable integration platforms to represent extracted features from videos, so that they could be indexed and searched. The task of indexing extracted features from videos is a difficult challenge, due to the diverse nature of the features and the temporal dimensions of videos. We present a semantic web based framework for automatic feature extraction, storage, indexing and retrieval of videos. Videos are represented as interconnected set of semantic resources. Furthermore, we suggest a new ranking algorithm for finding related resources which could be used in a semantic web based search engine. Finally, we define an algorithm for refinement of noise keywords to improve the quality of keywords. |
