3D interest points detection using symmetric surround-based surface saliency

Abstract

The detection of interest points is an important pre-processing step for the analysis of mesh surfaces. This paper proposes a new method for the detection of the interest points for 3D surface. Our method incorporates the Relative Distance-based Laplacian and to generate the symmetric surround-based surface saliency. The effectiveness of this method is demonstrated by studying the repeatability of the detected interest points under different perceptual conditions, such as different viewpoints and noise corruption. The results show that the proposed method achieves better performance than competitors. © 2013 Springer-Verlag.