This paper describes a study on the image searching behavior of end-users (journalists) and intermediaries (archivists) in a newspaper editorial office. Image queries by end-users and requests to intermediaries were analyzed, compared and categorized according to typologies from literature. The process of image selection was modeled and selection criteria were studied based on interviews, observation and a survey. The results indicate that most image queries and requests dealt with specific entities, but that object types were also common. Thematic image needs seem to be fulfilled by end-user searching and browsing rather than by requests. Image retrieval tasks were highly influenced by contextual factors. Relevance assessments were made at situational level using several types of criteria, including abstract and affective factors. Several types of collaborative searches were observed. Richer research and analysis methods are needed to characterize journalists' image needs and searching behavior.

This paper reports a study on the description and categorization of images. The aim of the study was to evaluate existing indexing frameworks in the context of reportage photographs and to find out how the use of this particular image genre influences the results. The effect of different tasks on image description and categorization was also studied. Subjects performed keywording and free description tasks and the elicited terms were classified using the most extensive one of the reviewed frameworks. Differences were found in the terms used in constrained and unconstrained descriptions. Summarizing terms such as abstract concepts, themes, settings and emotions were used more frequently in keywording than in free description. Free descriptions included more terms referring to locations within the images, people and descriptive terms due to the narrative form the subjects used without prompting. The evaluated framework was found to lack some syntactic and semantic classes present in the data and modifications were suggested. According to the results of this study image categorization is based on high-level interpretive concepts, including affective and abstract themes. The results indicate that image genre influences categorization and keywording modifies and truncates natural image description.Keywords: image content, free description, keywording, categorization, image categories, multidimensional scaling, hierarchical cluster analysis IntroductionThe digitalization of image collections has increased the availability of pictorial material for both commercial and research use. There exists a growing body of research into image retrieval and description. The nature of visual information, however, creates some special challenges. The range and type of attributes needed for describing image content is still under debate. Several frameworks have been created, yet their match with natural, unconstrained image descriptions formed by users has not been proved. The issue of attribute granularity is also challenging; on how many semantic levels should image access be provided? The meanings carried by images, the specificity of index terms, as well as the queries made to image collections may be of various levels. A query might request a specific item or an instance of a general category. It might also deal with a topical category of images or specify a particular abstract concept or affective response the image should evoke.The development of content-based image retrieval systems (i.e. systems that use visual image data to perform queries) has been an area of great interest during the last decade, but many challenges still remain. These include defining visual similarity so that it would match the users' mental models of similarity, as well as bridging the semantic gap between the higher-level semantic concepts used by people and the perceptual attributes addressed by the content-based algorithms. Domain and expected users are important in the development of image description and search tools. Systems and description schem...

This paper reports a study on the types of image categories constructed from magazine photographs. A novel sorting procedure was tested with the aim of providing more data on image similarity and possible category overlap. Expert and non-expert participants were compared in their categorizations. The new similarity sorting procedure resulted in an average of 67%-111% increase in similarity data gathered compared to basic free sorting. Categories were constructed on various levels of similarity: image Function, main visual content (People, Objects and Scene), conceptual content (Theme) and descriptors (Story, Affective, Description, Photography and Visual). Most categories were based on the theme and people portrayed in the photograph, and in the case of the expert subjects, image function. Also abstract and syntactic similarity criteria were employed by the subjects. The categories created by each subject showed on average a 35%-53% overlap. Participants also demonstrated a tendency to use multiple similarity criteria simultaneously and to combine terms from different levels in a single category name. These results indicate a need for a multifaceted approach in image categorization.

No abstract

No abstract