A connectionist model of associative storage and recall of 3D objects

A connectionist model which can store a sequence of various views of a 3D object is presented. The model consists of four components, each of which is realized as a network of neuron-like elements. The model can store several 3D objects in the same network in an overlapping manner. If the model is shown one view of a stored 3D object then a sequence of other views is recalled one by one. Since the storage is based on an associative matrix, the recall is possible even from an incomplete view. Instead of raw image data, a set of extracted features is stored