Developing methods for searching image databases is a challenging and ongoing area of research. A common approach is to use manual annotations, although generating annotations can be expensive in terms of time and money, and therefore may not be justified in many situations. Content-based search techniques which extract visual features from image data can be used, but users are typically forced to express their information need using example images, or through sketching interfaces. This can be difficult if no visual example of the information need is available, or when the information need cannot be easily drawn.   In this paper, we consider an alternative approach which allows a user to search for images through an intermediate database. In this approach, a user can search using text in the intermediate database as a way of finding visual examples of their information need. The visual examples can then be used to search a database that lacks annotations. Three experiments are presented which investigate this process. The first experiment automatically selects the image queries from the intermediary database; the second instead uses images which have been hand-picked by users. A third experiment, an interactive study, is then presented this study compares the intermediary interface to text search, where we consider text as an upper bound of performance. For this last study, an interface which supports the intermediary search process is described. Results show that while performance does not match manual annotations, users are able to find relevant material without requiring collection annotations.
['Robert Villa', 'Martin Halvey', 'Hideo Joho', 'David Hannah', 'Joemon M. Jose']
Can an intermediary collection help users search image databases without annotations