Perception and visualization of line images

This paper deals with state-of-the-art novel ideas of visualization, understanding and interpretation of two-dimensional (2D) line images. A new strategy using fast two-pass parallel pattern matching techniques is presented. It can learn, represent, visualize, and interpret 2D polyhedral line images with only very few learning samples. It can also distinguish similar patterns more accurately than other methods. Such a technique is applied to articulated object recognition and algorithms for articulated feature extraction are presented. Several illustrations are given and future research topics are discussed