Function-described graphs for modelling objects represented by sets of attributed graphs

We present in this article the model function-described graph (FDG), which is a type of compact representation of a set of attributed graphs (AGs) that borrow from random graphs the capability of probabilistic modelling of structural and attribute information. We de4ne the FDGs, their features and two distance measures between AGs (unclassi4ed patterns) and FDGs (models or classes) and we also explain an e6cient matching algorithm. Two applications of FDGs are presented: in the former, FDGs are used for modelling and matching 3D-objects described by multiple views, whereas in the latter, they are used for representing and recognising human faces, described also by several views. ? 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.