In this paper, we propose a multi-level abstraction mechanism for capturing the spatial and temporal semantics associated with various objects in an input image or in a sequence of video frames. This abstraction can m...
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In this paper, we propose a multi-level abstraction mechanism for capturing the spatial and temporal semantics associated with various objects in an input image or in a sequence of video frames. This abstraction can manifest itself effectively in conceptualizing events and views in multimedia data as perceived by individual users. The objective is to provide an efficient mechanism for handling content-based queries, with the minimum amount of processing performed on raw data during query evaluation. We introduce a multi-level architecture for video data management at different levels of abstraction. The architecture facilitates a multi-level indexing/searching mechanism. At the finest level of granularity, video data can be indexed based on mere appearance of objects and faces. For management of information at higher levels of abstractions, an object-oriented paradigm is proposed which is capable of supporting domain specific views.
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