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Extra resources for Representation and Retrieval of Video Data in Multimedia Systems

Example text

The same holds when other features are considered. In conclusion a distance normalization is necessary before of the application of user provided weights. An interesting approach based on the cooperation of models of different features {the society of models) has been proposed to solve this problem in [28, 37]. This approach has the main limitation in the need of rebuild all the underlying hierarchical data structure when a new image is added to the database. In this paper we present an original method to adequately weight the distances computed for each feature descriptor.

Aigrainetal. [1] also use arule system for video segmentation. Rules deal with temporally located information present in video frames. If adequately combined, these rules allow for identification of more macroscopical changes in the frame sequence and subsequent segmentation. i^vyxvi-VL- MPT •— 1 J 1 OUTPUT [ ->- b-+-J FRAME i+n Figure 2. The shot detector. Another model-based technique has been presented in [ 10, 11 ]. Here, video segmentation focuses on editing procedures during movie production, where editing phase contributes in a crucial manner to the creation of a semantics.

A structured conceptual schema for movie data based on a graph-like model is proposed also in [11, 12]. This hypermedia system exploits both a feature extraction engine, able to automatically detect some of the production characteristics of a movie, such as editing operations, and a user-guided iconic interface, that enables complex queries to be formulated, even without the knowledge of any formal query language. Other systems [7, 35, 45, 56] are more task-oriented; several of them have been proposed for storage and retrieval of faces.

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