The concept of visual classes for object classification

The article introduces the concept of visual classes asa general framework for object classification. Visual classes group together appearances which are similar with respect to a set of image measurements. As defined here, visual classes are implicit in many object representation schemes (geometric as well as appearance based models). We argue that the identification of visual classes provides a powerful tool for object classification. They provide a first step to classification depending on information provided for recognition, including context dependency and relations in space and time between objects. The article introduces a statistical object representation which can be seen as a generalization of various object representations. Based on this statistical representation, the article introduces a possible extraction and representation of visual classes. First experimental results are given in order to validate the concept.