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The paper describes a method for generating a generic deformable model from a training set of shapes depicted in a corpus of image sequences. Individual shapes in the training set are extracted automatically from the image sequences and represented by the control points of a B-spline surface. The generic model is derived by principal component analysis on the aligned training shapes. Using the acquired generic models, 3-D shape recovery, tracking and object identification are implemented within one procedure. Experimental results are presented both for generation and application of the model within the domain of vehicles appearing in traffic scenes.