Decomposed contour prior for shape recognition

Zhi Yang, Yu Kong, Yun Fu

Abstract: In this paper, we address the problem of representing objects using contours for the purpose of recognition. We propose a novel segmentation method for integrating a new contour matching energy into level set based segmentation schemes. The contour matching energy is represented by major components of Elliptic Fourier shape descriptors and serves as a shape prior to guide the curve evolution. The contours in training dataset serve as templates and are utilized to infer the category of an unknown image based on matching. Our method is evaluated on the UCF sports dataset and Caltech 101 dataset. Experiments show that our method achieves promising recognition accuracy and is robust to noisy low-level features and background clutter.