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Conference Papers Year : 2011

IRIM at TRECVID 2011: Semantic Indexing and Instance Search

Miriam Redi
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Lionel Granjon
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Hervé Jégou
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Matthieu Cord


The IRIM group is a consortium of French teams work- ing on Multimedia Indexing and Retrieval. This paper describes its participation to the TRECVID 2011 se- mantic indexing and instance search tasks. For the semantic indexing task, our approach uses a six-stages processing pipelines for computing scores for the likeli- hood of a video shot to contain a target concept. These scores are then used for producing a ranked list of im- ages or shots that are the most likely to contain the tar- get concept. The pipeline is composed of the following steps: descriptor extraction, descriptor optimization, classification, fusion of descriptor variants, higher-level fusion, and re-ranking. We evaluated a number of dif- ferent descriptors and tried different fusion strategies. The best IRIM run has a Mean Inferred Average Pre- cision of 0.1387, which ranked us 5th out of 19 partic- ipants. For the instance search task, we we used both object based query and frame based query. We formu- lated the query in standard way as comparison of visual signatures either of object with parts of DB frames or as a comparison of visual signatures of query and DB frames. To produce visual signatures we also used two apporaches: the first one is the baseline Bag-Of-Visual- Words (BOVW) model based on SURF interest point descriptor; the second approach is a Bag-Of-Regions (BOR) model that extends the traditional notion of BOVW vocabulary not only to keypoint-based descrip- tors but to region based descriptors.
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hal-00677651 , version 1 (10-05-2012)


  • HAL Id : hal-00677651 , version 1


Bertrand Delezoide, Frédéric Precioso, Philippe-Henri Gosselin, Miriam Redi, Bernard Merialdo, et al.. IRIM at TRECVID 2011: Semantic Indexing and Instance Search. TRECVID 2011 - TREC Video Retrieval Evaluation Online, Nov 2011, Gaithersburg, MD, United States. 12p. ⟨hal-00677651⟩
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