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Communication Dans Un Congrès Année : 2012

IRIM at TRECVID 2012: Semantic Indexing and Instance Search

Miriam Redi
  • Fonction : Auteur
  • PersonId : 765821
  • IdRef : 171913272
Bernard Merialdo
  • Fonction : Auteur
  • PersonId : 930765
Hervé Jégou
  • Fonction : Auteur
  • PersonId : 833473
Matthieu Cord
Liming Chen

Résumé

The IRIM group is a consortium of French teams work- ing on Multimedia Indexing and Retrieval. This paper describes its participation to the TRECVID 2012 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, classi cation, fusion of descriptor variants, higher-level fusion, and re-ranking. We evaluated a number of dif- ferent descriptors and tried di erent fusion strategies. The best IRIM run has a Mean Inferred Average Pre- cision of 0.2378, which ranked us 4th out of 16 partici- pants. For the instance search task, our approach uses two steps. First individual methods of participants are used to compute similrity between an example image of in- stance and keyframes of a video clip. Then a two-step fusion method is used to combine these individual re- sults and obtain a score for the likelihood of an instance to appear in a video clip. These scores are used to ob- tain a ranked list of clips the most likely to contain the queried instance. The best IRIM run has a MAP of 0.1192, which ranked us 29th on 79 fully automatic runs.
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Dates et versions

hal-00770258 , version 1 (04-01-2013)

Identifiants

  • HAL Id : hal-00770258 , version 1

Citer

Nicolas Ballas, Benjamin Labbé, Aymen Shabou, Hervé Le Borgne, Philippe-Henri Gosselin, et al.. IRIM at TRECVID 2012: Semantic Indexing and Instance Search. TRECVID - TREC Video Retrieval Evaluation workshop, Nov 2012, Gaithersburg, MD, United States. 12p. ⟨hal-00770258⟩
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