IRIM at TRECVID 2015: Semantic Indexing - Archive ouverte HAL
Communication Dans Un Congrès Année : 2015

IRIM at TRECVID 2015: Semantic Indexing

Miriam Redi
  • Fonction : Auteur
  • PersonId : 765821
  • IdRef : 171913272
Abdelkader Hamadi
  • Fonction : Auteur
  • PersonId : 955237
Liming Chen

Résumé

The IRIM group is a consortium of French teams supported by the GDR ISIS and working on Multimedia Indexing and Retrieval. This paper describes its participation to the TRECVID 2015 semantic indexing (SIN). 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, classification, 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 0.2947, which ranked it 4th out of 15 participants.
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Dates et versions

hal-01233398 , version 1 (23-08-2018)

Identifiants

  • HAL Id : hal-01233398 , version 1

Citer

Hervé Le Borgne, Philippe Gosselin, David Picard, Miriam Redi, Bernard Mérialdo, et al.. IRIM at TRECVID 2015: Semantic Indexing. Proceedings of TRECVid, Nov 2015, Gaithersburg, MD, United States. ⟨hal-01233398⟩
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