Ontology-driven Annotation and Access of Presentation Video Data

The tremendous growth in video data calls for efficient and flexible access mechanisms. In this paper, we propose an ontology-driven framework for presentation video annotation and access. The goal is to integrate ontology into video systems to improve users’ video access experience. To realize ontology-driven video annotation, the first and foremost step is video segmentation. Current research in video segmentation has mainly focused on the visual and/or auditory modalities. In this paper, we investigate how to combine visual and textual information in the hierarchical segmentation of presentation video data. With average F-scores over 0.92, our experiments show that the proposed segmentation procedure is effective. After a video is segmented, video annotation data can be extracted. To extract annotation data from a video and its segments, and to organize them in a way that facilitates video access, we propose a multiontology based multimedia annotation model. In this model, a domain-independent multimedia ontology is integrated with multiple domain ontologies. The goal is to provide multiple, domain-specific views of the same multimedia content and, thus, better address different users’ information needs. With extracted annotation data, ontology-driven video access explores domain knowledge embedded in domain ontologies and tailors the video access to the specific needs of individual users from different domains. Our experience suggests that ontology-driven video access can improve video retrieval relevancy and, thus, enhance users’ video access experience.