The ImageCLEF 2015 Scalable Image Annotation, Localization and Sentence Generation task was the fourth edition of a challenge aimed at developing more scalable image annotation systems. In particular this year the focus of the three subtasks available to participants had the goal to develop techniques to allow computers to reliably describe images, localize the different concepts depicted in the images and generate a description of the scene. All three tasks use a single mixed modality data source of 500,000 web page items which included raw images, textual features obtained from the web pages on which the images appeared, as well as various visual features extracted from the images themselves. Unlike previous years the test set was also the training set and in this edition of the task hand-labelled data has been allowed. The images were obtained from the Web by querying popular image search engines. The development and subtasks 1 and 2 test sets were both taken from the "training set" and had 1,979 and 3,070 samples, and the subtask 3 track had 500 and 450 samples. The 251 concepts this year were chosen to be visual objects that are localizable and that are useful for generating textual descriptions of visual content of images and were mined from the texts of our large database of image-webpage pairs. This year 14 groups participated in the task, submitting a total of 122 runs across the 3 subtasks and 11 of the participants also submitted working notes papers. This result is very positive, in fact if compared to the 11 participants and 58 submitted runs of the last year it is possible to see how the interest in this topic is still very high.

Overview of the ImageCLEF 2015 Scalable Image Annotation, Localization and Sentence Generation task

Piras, Luca;
2015-01-01

Abstract

The ImageCLEF 2015 Scalable Image Annotation, Localization and Sentence Generation task was the fourth edition of a challenge aimed at developing more scalable image annotation systems. In particular this year the focus of the three subtasks available to participants had the goal to develop techniques to allow computers to reliably describe images, localize the different concepts depicted in the images and generate a description of the scene. All three tasks use a single mixed modality data source of 500,000 web page items which included raw images, textual features obtained from the web pages on which the images appeared, as well as various visual features extracted from the images themselves. Unlike previous years the test set was also the training set and in this edition of the task hand-labelled data has been allowed. The images were obtained from the Web by querying popular image search engines. The development and subtasks 1 and 2 test sets were both taken from the "training set" and had 1,979 and 3,070 samples, and the subtask 3 track had 500 and 450 samples. The 251 concepts this year were chosen to be visual objects that are localizable and that are useful for generating textual descriptions of visual content of images and were mined from the texts of our large database of image-webpage pairs. This year 14 groups participated in the task, submitting a total of 122 runs across the 3 subtasks and 11 of the participants also submitted working notes papers. This result is very positive, in fact if compared to the 11 participants and 58 submitted runs of the last year it is possible to see how the interest in this topic is still very high.
2015
Computer Science (all)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/254943
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