FEATURE SPACE TRAJECTORY FOR DISTORTED-OBJECT CLASSIFICATION AND POSEESTIMATION IN SYNTHETIC-APERTURE RADAR

Classification and pose estimation of distorted input objects are cons idered. The feature space trajectory representation of distorted views of an object is used with a new eigenfeature space. For a distorted i nput object, the closest trajectory denotes the class of the input and the closest line segment on it denotes its pose. If an input point is too far from a trajectory, it is rejected as clutter. New methods for selecting Fukunaga-Koontz discriminant vectors, the number of dominan t eigenvectors per class al-td for determining training, and test set compatibility are presented. (C) 1997 Society of Photo-Optical Instrum entation Engineers.