Study on intelligent video retrieval system based on semantic representation of video data

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An important issue in multimedia information systems is the lack of models for semantic representation of multimedia objects to enable the search and retrieval of an appropriate multimedia object from large archives. In this research, we have studied on various aspects especially concerning video data. In our system, the typical scene is annotated by connected graph structures where graph nodes correspond to specific Affect Units. An Affect unit is an abstraction of affective causality. Our video description model is implemented based on the ideas of "object- oriented model with prototypes" which is proposed in the field of object-oriented programming. Prototype is a prefabricated object with predefined structure, contents, and behavior, from which new objects can be created by copying the prototype. By using the prototype annotation, our system enables users to create semantic representations of video content, group related sets of scene descriptors hierarchically, use these descriptors to annotate video content, and reuse descriptive effort. By using our semantic representation of video content, the database can provide the user three types of retrieval tools : keyword-based, story-based, and both-mixtured.