Abstract
In this work we propose a new approach to model video data. To interpret the video semantic, we propose to model the video on the basis of the underlying dynamics contained in the video. Thus, the video is seen as a measurement of properties of objects embedded in the video and of their behaviors over time. The objects' behaviors are described by states and state transitions using statechart diagram. Then, this diagram is used to partition the video into meaningful segments. For efficient retrieval of information, we propose to use indexes based on the states of objects. The proposed model thus helps to store information about similar types of video data in a single database schema and supports content-based querying from a repository of video data.
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