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Overview of the ImageCLEF 2007 Object Retrieval Task

2008; Springer Science+Business Media; Linguagem: Inglês

10.1007/978-3-540-85760-0_58

1611-3349

Thomas Deselaers, Allan Hanbury, Ville Viitaniemi, András A. Benczúr, Mátyás Brendel, Bálint Daróczy, Hugo Jair Escalante Balderas, Theo Gevers, Carlos Hernández, Steven C. H. Hoi, Jorma Laaksonen, Mingjing Li, Heidy Marisol Marín Castro, Hermann Ney, Xiaoguang Rui, Nicu Sebe, Julian Stöttinger, Lei Wu,

Multimodal Machine Learning Applications

We describe the object retrieval task of ImageCLEF 2007, give an overview of the methods of the participating groups, and present and discuss the results. The task was based on the widely used PASCAL object recognition data to train object recognition methods and on the IAPR TC-12 benchmark dataset from which images of objects of the ten different classes bicycles, buses, cars, motorbikes, cats, cows, dogs, horses, sheep, and persons had to be retrieved. Seven international groups participated using a wide variety of methods. The results of the evaluation show that the task was very challenging and that different methods for relevance assessment can have a strong influence on the results of an evaluation.