| The tremendous growth in multimedia data calls for efficient and flexible access mechanisms. In this dissertation, we propose an ontology-driven framework for 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 dissertation, we investigate how to combine visual, auditory, and textual information in the segmentation of educational video data. Experiments show that text-based segmentation generally decomposes videos into semantic segments, which facilitates video content understanding and video annotation data extraction.; To extract annotation data from videos and video segments, and to organize them in a way that facilitates video access, we propose a multi-ontology based multimedia annotation model. In this model, domain-independent multimedia ontology is integrated with multiple domain-dependent ontologies. Preliminary evaluation suggests that multi-ontology based multimedia annotation provides multiple, domain-specific views of the same multimedia content and, thus, better meets different users' information needs.; With extracted annotation data, ontology-driven video access explores domain knowledge embedded in domain ontology and tailors the video access to the specific needs of individual users from different domains. Our experience shows that ontology-driven video access can improve video retrieval relevancy and, thus, enhance users' video access experience. |
