Slinky-based Segmentation on 3D Polygonal Model for Functional Parts in Computer Graphics

Abstract

Segmenting three-dimensional (3D) polygonal model into meaningful functional parts is
greatly debated in year 2010. Yet, there is no robust segmentation algorithm as to satisfactorily match
the result to the human desired segments. This paper breaks the model into human definable
functional parts (or features). The proposed method first shrinks the model into triangular-skeleton by
Laplacian-based contraction method. The edge-collapsed and vertex-merging of simplification are
applied to turn the skeleton into single-connected edges and merge the linear skeleton nodes for fast
processing respectively. Slinky-based segmentation method is applied to investigate the contour and
segment both the periphery and centered features. The generated result is compared to the seven wellknown
segmentation methods and the results are consistent and stable throughout all the models