Semantic access of frontal face images: the expression-invariant problem

Semantic queries to a database of images are more desirable than low-level feature queries, because they facilitate the user´s task. One such approach is object-related image retrieval. In the context of face images, it is of interest to retrieve images based on people´s names and facial expressions. However, when images of the database are allowed to appear at different facial expressions, the face recognition approach encounters the expression-invariant problem, i.e. how to robustly identify a person´s face for which its learning and testing face images differ in facial expression. This paper presents a new local, probabilistic approach that accounts for this (as well as other previous studied) difficulty