Three-dimensional salient point detection based on the Laplace–Beltrami eigenfunctions.

Three-dimensional (3D) salient point detection is a fundamental problem in computer graphics and computer vision. We propose a new method using the Laplace–Beltrami eigenfunctions for detecting the salient points of 3D models. We compute the extrema of the low-frequency Laplace–Beltrami eigenfunctions and remove the redundancy of the extrema. Merging the extrema of the eigenfunctions, we keep the extrema appearing simultaneously on no less than a certain number of eigenfunctions as the candidate salient points. Clustering these extrema, we consider the representatives of the clusters as the final salient points. Our experimental results demonstrate that the proposed method is effective for 3D salient point detection. Besides that, some experiments are also conducted to verify that the proposed method is insensitive to small boundary noise. [ABSTRACT FROM AUTHOR]