%0 Journal Article %1 Hollink2004Classification %A Hollink, L. %A Schreiber, Th A. %A Wielinga, B. J. %A Worring, M. %D 2004 %J International Journal of Human-Computer Studies %K annotation diss evaluation image mtg07-paper retrieval samt-kat-demo samt-paper %N 5 %T Classification of user image descriptions %V 61 %X In order to resolve the mismatch between user needs and current image retrieval techniques, we conducted a study to get more information about what users look for in images. First, we developed a framework for the classification of image descriptions by users, based on various classification methods from the literature. The classification framework distinguishes three related viewpoints on images, namely nonvisual metadata, perceptual descriptions and conceptual descriptions. For every viewpoint a set of descriptive classes and relations is specified. We used the framework in an empirical study, in which image descriptions were formulated by 30 participants. The resulting descriptions were split into fragments and categorized in the framework. The results suggest that users prefer general descriptions as opposed to specific or abstract descriptions. Frequently used categories were objects, events and relations between objects in the image.

@article{Hollink2004Classification, abstract = {In order to resolve the mismatch between user needs and current image retrieval techniques, we conducted a study to get more information about what users look for in images. First, we developed a framework for the classification of image descriptions by users, based on various classification methods from the literature. The classification framework distinguishes three related viewpoints on images, namely nonvisual metadata, perceptual descriptions and conceptual descriptions. For every viewpoint a set of descriptive classes and relations is specified. We used the framework in an empirical study, in which image descriptions were formulated by 30 participants. The resulting descriptions were split into fragments and categorized in the framework. The results suggest that users prefer general descriptions as opposed to specific or abstract descriptions. Frequently used categories were objects, events and relations between objects in the image.}, added-at = {2010-01-11T12:37:36.000+0100}, at = {2007-06-20 13:11:34}, author = {Hollink, L. and Schreiber, Th A. and Wielinga, B. J. and Worring, M.}, biburl = {https://www.bibsonomy.org/bibtex/2fafee8650ebcf3d02f7d72936660c4da/sschenk}, description = {diss}, id = {1400842}, interhash = {1ab800f28ff655168fd6f954859bd18b}, intrahash = {fafee8650ebcf3d02f7d72936660c4da}, journal = {International Journal of Human-Computer Studies}, keywords = {annotation diss evaluation image mtg07-paper retrieval samt-kat-demo samt-paper}, number = 5, priority = {2}, timestamp = {2010-01-11T12:38:03.000+0100}, title = {Classification of user image descriptions}, volume = 61, year = 2004 }