Knowledge representation and annotation of multimedia documents typically have been pursued in two different directions. Previous approaches have focused either on low level descriptors, such as dominant color, or on the semantic content dimension and corresponding manual annotations, such as person or vehicle. In this paper, we present a knowledge infrastructure and a experimentation platform for semantic annotation to bridge the two directions. Ontologies are being extended and enriched to include low-level audiovisual features and descriptors. Additionally, we present a tool that allows for linking low-level MPEG-7 visual descriptions to ontologies and annotations. This way we construct ontologies that include prototypical instances of high-level domain concepts together with a formal specification of the corresponding visual descriptors. This infrastructure is exploited by a knowledge-assisted analysis framework that may handle problems like segmentation, tracking, feature extraction and matching in order to classify scenes, identify and label objects, thus automatically create the associated semantic metadata.