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Communication Dans Un Congrès Année : 2000

Statistical motion-based video indexing and retrieval

Résumé

We propose an original approach for the characterization of video dynamic content with a view to supplying new functionalities for motion-based video indexing and retrieval with query by example. We have designed a statistical framework for motion content description without any prior motion segmentation, and for motion-based video classification and retrieval. Contrary to other proposed methods, we do not extract from a given video sequence a set of motion features but we identify a global probabilistic model, expressed as a temporal Gibbs random field. This leads to define an efficient statistical motion-based similarity measure, relying on the computation of conditional likelihoods, to discriminate various motion contents. We have carried out experiments on a set of 100 video sequences, representative of various motion situations (temporal textures as fire and crowd motions, sport videos, car sequences, low motion activity examples)
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Dates et versions

hal-02283233 , version 1 (10-09-2019)

Identifiants

  • HAL Id : hal-02283233 , version 1

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Ronan Fablet, Patrick Bouthemy, Patrick Pérez. Statistical motion-based video indexing and retrieval. RIAO'2000 : conference on content-based multimedia information acces, Apr 2000, Paris, France. pp.602 - 619. ⟨hal-02283233⟩
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