Title of article :
The segmented and annotated IAPR TC-12 benchmark
Author/Authors :
Escalante، نويسنده , , Hugo Jair and Hernلndez، نويسنده , , Carlos A. and Gonzalez، نويسنده , , Jesus A. and Lَpez-Lَpez، نويسنده , , A. and Montes، نويسنده , , Manuel and Morales، نويسنده , , Eduardo F. and Enrique Sucar، نويسنده , , L. and Villaseٌor، نويسنده , , Luis and Grubinger، نويسنده , , Michael، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2010
Abstract :
Automatic image annotation (AIA), a highly popular topic in the field of information retrieval research, has experienced significant progress within the last decade. Yet, the lack of a standardized evaluation platform tailored to the needs of AIA, has hindered effective evaluation of its methods, especially for region-based AIA. Therefore in this paper, we introduce the segmented and annotated IAPR TC-12 benchmark; an extended resource for the evaluation of AIA methods as well as the analysis of their impact on multimedia information retrieval. We describe the methodology adopted for the manual segmentation and annotation of images, and present statistics for the extended collection. The extended collection is publicly available and can be used to evaluate a variety of tasks in addition to image annotation. We also propose a soft measure for the evaluation of annotation performance and identify future research areas in which this extended test collection is likely to make a contribution.
Keywords :
Automatic image annotation , Image retrieval , Evaluation metrics , Data set creation , Ground truth collection
Journal title :
Computer Vision and Image Understanding
Journal title :
Computer Vision and Image Understanding