Boundary Finding with Parametrically Deformable Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active shape models—their training and application
Computer Vision and Image Understanding
Classifier and shift-invariant automatic target recognition neural networks
Neural Networks - Special issue: automatic target recognition
Efficient Simplicial Reconstructions of Manifolds from Their Samples
IEEE Transactions on Pattern Analysis and Machine Intelligence
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The complexity in variation that objects are provided with motivates to consider learning strategies when modeling their shape. This paper evaluates auto-associative neural networks and their application to shape analysis. Previously, such networks have been considered in connection with 'point distribution models' for describing two-dimensional contours in a statistical manner. This paper suggests an extension of this idea to achieve a more flexible model that is independent of landmarks.