HYBRID AUDIO-VISUAL CATEGORIZATION SYSTEM AND METHOD
First Claim
1. A method of producing a set of tags for an input audiovisual file, the set of tags indicating values of attributes of an audiovisual work of defined type represented by said audiovisual file, the method comprising the steps of:
- providing an initial estimate of the values of the respective attributes of the audiovisual work represented by said audiovisual file;
applying a set of one or more correlation functions to the attribute-value estimates of said initial estimate, to produce a set of revised estimates; and
outputting the final result of the applying step as the set of tags for said input audiovisual file;
wherein the correlation functions applied in said applying step are functions embodying the correlations holding between known attribute-values of a set of training examples, said training examples being audiovisual works of said defined type corresponding to manually-tagged audiovisual files.
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Abstract
Meta-data (tags) for an audiovisual file can be generated by producing an initial estimate of the tags and then revising the estimate (notably to expand it and/or render it more precise) based on the assumption that the relationships which hold between the different tags for a set of manually-tagged training examples will also hold for the tags of the input file now being tagged. A fully-automatic method and system is a hybrid between signal-based and machine-learning approaches, because the initial tag estimate is based on the physical properties of the signal representing the audiovisual file. The initial tag estimate may be produced by inferring that the input content will have the same tags as those files of the same kind, in the training database, which have a global similarity to the input audiovisual file in terms of signal properties.
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Citations
11 Claims
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1. A method of producing a set of tags for an input audiovisual file, the set of tags indicating values of attributes of an audiovisual work of defined type represented by said audiovisual file, the method comprising the steps of:
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providing an initial estimate of the values of the respective attributes of the audiovisual work represented by said audiovisual file;
applying a set of one or more correlation functions to the attribute-value estimates of said initial estimate, to produce a set of revised estimates; and
outputting the final result of the applying step as the set of tags for said input audiovisual file;
wherein the correlation functions applied in said applying step are functions embodying the correlations holding between known attribute-values of a set of training examples, said training examples being audiovisual works of said defined type corresponding to manually-tagged audiovisual files. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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Specification