Structural and Event Based Multimodal Video Data Modeling

Abstract

Investments on multimedia technology enable us to store many more reflections of the real world in digital world as videos. By recording videos about real world entities, we carry a lot of information to the digital world directly. In order to store and efficiently query this information, a video database system (VDBS) is necessary. In this thesis work, we propose a structural, event based and multimodal (SEBM) video data model for VDBSs. SEBM video data model supports three different modalities that are visual, auditory and textual modalities and we propose that we can dissolve these three modalities with a single SEBM video data model. This proposal is supported by the interpretation of the video data by human. Hence we can answer the content based, spatio-temporal and fuzzy queries of the user more easily, since we store the video data as the way that s/he interprets the real world data. We follow divide and conquer technique when answering very complicated queries. We have implemented the SEBM video data model in a Java based system that uses XML for representing the SEBM data model and Berkeley XML DBMS for storing the data based on the SEBM prototype system.

An intelligent fuzzy object-oriented database framework for video database applications

“…In [4,46], the SEBM model, which is a structural and event-based multimodal data model, is introduced. The model includes several sub models to model the structure of video data.…”