The first image retrieval systems hold the advantage of being fully automatic, and thus scalable to large collections of images but are restricted to the representation of low-level aspects (e.g. colors, textures...) without considering the semantic content of images. This obviously compromises interaction, making it difficult for a user to query with precision. The growing need for `intelligent' systems, i.e. being capable of bridging this semantic gap, leads to new architectures combining multiple characterizations of the image content. This paper presents SIAIR, a promising highlevel framework featuring semantics, signal color and spatial characterizations. It features a fully-textual query module based on a language manipulating both boolean and quantification operators, therefore making it possible for a user to request elaborate image scenes such as a "covered(mostly grey) sky" or "people in front of a building". KEYWORDS Multimedia, Image Retrieval, Aut...