3-D object recognition from range images by using a model-based Hopfield-style matching algorithm

A new method is proposed for recognizing 3-D objects by using a Hopfield-style optimization algorithm based on matching between patch-based image and model descriptions. To obtain the image descriptions, range images are employed to extract reliable high-level patch features. In the optimization process the objective function is a Liapunov function that is minimized in a Hopfield net with its interconnections encoding the imposed geometrical constraints on the model descriptions. At first, the paper describes a pre-processing method for deriving the necessary image description. It then presents the structure of the used Hopfield net which is able to recognize multiple objects all at once