RECENT PROGRESSES IN SKEWED SYMMETRY DETECTION
Atr State · 2001
Symmetry is a basic shape feature of objects. Shape representation and object recognition based on symmetry is an important research area in patttern recognition and artificial intelligence. The projections of the symmetrical surfaces of 3-D objects always show as skewed-symmetry in image plane. Using skewed symmetry information we can quicken the procedures such as object pose estimation, direction computation and image registration. In this paper, we describe in detail the forming models and representation techniques of skewed symmetry and then introduce three newly appeared main detection approaches, which are the one based on Hough transform, the one based on invariant signatures and the one based on regularization. We also give the possible directions of further studies after we introduce their main ideas, the data to be processed, and their merits and shortcomings.