Image retrieval has commonly been attempted using non-semantic approaches. It is clear though, that semantic retrieval is more desirable because it facilitates the user's task. In this paper, we present a new approach to semantic access of a database of images by asking for the presence of certain objects; this is known as object-related image retrieval. This approach is built within a classical computer vision framework i.e. localization, segmentation and identi cation. This platform is used to automatically index images of a given database by object names, which nally allows the use of semantics driven by these object names to extract images from the database e.g. all those images that have a bull and Melissa's face". The use of a totally automatic system would cause some errors of indexing and so retrieval. To solve this we use a human-in-the-loop strategy where a human expert is placed after the two outputs of the system to con rm their correctness". An experim...
Aleix M. Martínez, Joan R. Serra