FORMS - A FLEXIBLE OBJECT RECOGNITION AND MODELING SYSTEM

We describe a flexible object recognition and modelling system (FORMS) which represents and recognizes animate objects from their silhouette s. This consists of a model for generating the shapes of animate objec ts which gives a formalism for solving the inverse problem of object r ecognition. We model all objects at three levels of complexity: (i) th e primitives, (ii) the mid-grained shapes, which are deformations of t he primitives, and (iii) objects constructed by using a grammar to joi n mid-grained shapes together. The deformations of the primitives can be characterized by principal component analysis or modal analysis. Wh en doing recognition the representations of these objects are obtained in a bottom-up manner from their silhouettes by a novel method for sk eleton extraction and part segmentation based on deformable circles. T hese representations are then matched to a database of prototypical ob jects to obtain a set of candidate interpretations. These interpretati ons are verified in a top-down process. The system is demonstrated to be stable in the presence of noise, the absence of parts, the presence of additional parts, and considerable variations in articulation and viewpoint. Finally, we describe how such a representation scheme can b e automatically learnt from examples.