Please use this identifier to cite or link to this item: http://inaoe.repositorioinstitucional.mx/jspui/handle/1009/1401
The segmented and annotated IAPR TC-12 benchmark
HUGO JAIR ESCALANTE BALDERAS
CARLOS ARTURO HERNANDEZ GRACIDAS
JESUS ANTONIO GONZALEZ BERNAL
AURELIO LOPEZ LOPEZ
MANUEL MONTES Y GOMEZ
EDUARDO FRANCISCO MORALES MANZANARES
LUIS ENRIQUE SUCAR SUCCAR
LUIS VILLASEÑOR PINEDA
Acceso Abierto
Atribución-NoComercial-SinDerivadas
Data set creation
Ground truth collection
Evaluation metrics
Automatic image annotation
Image retrieval
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.
Elsevier Inc.
2010
Artículo
Inglés
Estudiantes
Investigadores
Público en general
Escalante-Balderas, H.J., et al., (2010). The segmented and annotated IAPR TC-12 benchmark, Computer Vision and Image Understanding, (114): 419–428
CIENCIA DE LOS ORDENADORES
Versión aceptada
acceptedVersion - Versión aceptada
Appears in Collections:Artículos de Ciencias Computacionales

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