Statistical Motion-Based Retrieval with Partial Query

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Statistical Motion-Based Retrieval with Partial Query
We present an original approach for motion-based retrieval involving partial query. More precisely, we propose an uni ed statistical framework both to extract entities of interest in video shots and to achieve the associated content-based characterization to be exploited for retrieval issues. These two stages rely on the characterization of scene activity in video sequences based on a non-parametric statistical modeling of motion information. Areas comprising relevant scene activity are extracted from an ascendant hierarchical classi cation applied to the adjacency graph of an initial block-based partition of the image. Therefore, given a video base, we are able to construct a base of samples of entities of interest characterized by their associated scene activity model. The retrieval operations is then formulated as a Bayesian inference issue using the MAP criterion. We report di erent results of extraction of entities of interest in video sequences and examples of retrieval operation...
Ronan Fablet, Patrick Bouthemy
Added 26 Aug 2010
Updated 26 Aug 2010
Type Conference
Year 2000
Authors Ronan Fablet, Patrick Bouthemy
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