TY - CHAP
T1 - Coordinated multiple views to support image retrieval
AU - Eler, Danilo Medeiros
AU - Prates, Jorge Marques
AU - Garcia, Rogerio Eduardo
AU - Minghim, Rosane
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/9/18
Y1 - 2014/9/18
N2 - The number of images available has grown over the years, as well as the number of techniques to aid to organizing and retrieving from image collections. Techniques and systems have been proposed to recover images based on query, in which an image (or words) is used as input parameter and a list of similar images (or images with related text content) is recovered. However, understanding how the retrieved images are related to each other remains as a problem. This paper proposes an approach based on multidimensional visualization and coordination techniques to show the relationship from retrieved images. In this approach, coordination techniques are employed to perform image retrieval methods and highlight the results in visual representations, showing how retrieved images are relate. To evaluate our proposal image collections with and without textual annotations related to each image were used, and also image retrieval mechanisms based on distance, topic and semantic to retrieve images from distinct and multimodal datasets.
AB - The number of images available has grown over the years, as well as the number of techniques to aid to organizing and retrieving from image collections. Techniques and systems have been proposed to recover images based on query, in which an image (or words) is used as input parameter and a list of similar images (or images with related text content) is recovered. However, understanding how the retrieved images are related to each other remains as a problem. This paper proposes an approach based on multidimensional visualization and coordination techniques to show the relationship from retrieved images. In this approach, coordination techniques are employed to perform image retrieval methods and highlight the results in visual representations, showing how retrieved images are relate. To evaluate our proposal image collections with and without textual annotations related to each image were used, and also image retrieval mechanisms based on distance, topic and semantic to retrieve images from distinct and multimodal datasets.
KW - Coordinated Multiple Views
KW - Coordination Techniques
KW - Image Retrieval
KW - Linked Views
KW - Multimodal Dataset
UR - https://www.scopus.com/pages/publications/84912077806
U2 - 10.1109/IV.2014.48
DO - 10.1109/IV.2014.48
M3 - Chapter
AN - SCOPUS:84912077806
T3 - Proceedings of the International Conference on Information Visualisation
SP - 139
EP - 144
BT - Proceedings - 2014 18th International Conference on Information Visualisation
A2 - Banissi, Ebad
A2 - Bannatyne, Mark W. McK.
A2 - Marchese, Francis T.
A2 - Sarfraz, Muhammad
A2 - Ursyn, Anna
A2 - Venturini, Gilles
A2 - Wyeld, Theodor G.
A2 - Cvek, Urska
A2 - Trutschl, Marjan
A2 - Grinstein, Georges
A2 - Geroimenko, Vladimir
A2 - Kenderdine, Sarah
A2 - Kenderdine, Sarah
A2 - Kenderdine, Sarah
A2 - Bouali, Fatma
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 18th International Conference on Information Visualisation: Visualisation, BioMedical Visualization, Visualisation on Built and Rural Environments and Geometric Modelling and Imaging, IV 2014
Y2 - 16 July 2014 through 18 July 2014
ER -