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IRIM at TRECVID 2013: Semantic Indexing and Instance Search

Abstract : The IRIM group is a consortium of French teams working on Multimedia Indexing and Retrieval. This paper describes its participation to the TRECVID 2013 semantic indexing and instance search tasks. For the semantic indexing task, our approach uses a six-stages processing pipelines for computing scores for the likelihood of a video shot to contain a target concept. These scores are then used for producing a ranked list of images or shots that are the most likely to contain the target concept. The pipeline is composed of the following steps: descriptor extraction, descriptor optimization, classiffication, fusion of descriptor variants, higher-level fusion, and re-ranking. We evaluated a number of different descriptors and tried different fusion strategies. The best IRIM run has a Mean Inferred Average Precision of 0.2796, which ranked us 4th out of 26 participants.
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https://hal.inria.fr/hal-00953092
Contributor : Marie-Christine Fauvet <>
Submitted on : Monday, March 3, 2014 - 2:23:12 PM
Last modification on : Friday, July 3, 2020 - 4:49:19 PM
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  • HAL Id : hal-00953092, version 1

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Nicolas Ballas, Benjamin Labbé, Hervé Le Borgne, Philippe Gosselin, Miriam Redi, et al.. IRIM at TRECVID 2013: Semantic Indexing and Instance Search. Proc. TRECVID Workshop, 2013, Gaithersburg, MD, United States. ⟨hal-00953092⟩

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