Object recognition in image sequences with cellular neural networks

In this paper, the application of CNN associative memories for 3D object re cognition is presented. The main idea is to analyse the optical flow in an image sequence of an object. Several features of the optical flow between t wo succeeding images are calculated and merged to a time series of features for the whole image sequence. These features show several object specific characteristics and are used for a classification step in an object recogni tion system. Therefore, the feature vectors of an object set are learnt and recalled by an associative memory based on the paradigm of cellular neural networks (CNN). (C) 2000 Elsevier Science B.V. All rights reserved.