2D shape matching by contour flexibility.
In computer vision, shape matching is a challenging problem, especially when articulation and deformation of parts occur. These variations may be insignificant in terms of human recognition, but often cause a matching algorithm to give results that are inconsistent with our perception. In this paper, we propose a novel shape descriptor of planar contours, called contour flexibility, which represents the deformable potential at each point along a contour. With this descriptor, The local and global features can be obtained from the contour. We then present a shape matching scheme based on the features obtained. Experiments with comparisons to recently published algorithms show that our algorithm performs best.
Xu
Chunjing
C
Department of Information Engineering, The Chinese University of Hong Kong, Hong Kong. cjxu6@ie.cuhk.edu.hk
Liu
Jianzhuang
J
Tang
Xiaoou
X
D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated / Q000379:methods*; D013382:Subtraction Technique