3D Mesh segmentation has become an important research field in computer graphics during the past few decades. Many geometry based and semantic oriented approaches for 3D mesh segmentation has been presented. However, only a few algorithms based on Markov Random Field (MRF) has been presented for 3D object segmentation. In this letter, we present a definition of mesh segmentation according to the labeling problem. Inspired by the capability of MRF combining the geometric information and the topology information of a 3D mesh, we propose a novel 3D mesh segmentation model based on MRF and Graph Cuts. Experimental results show that our MRF-based schema achieves an effective segmentation.

Mesh segmentation is a foundational operation for many computer graphics applications. Although various automatic segmentation schemes have been proposed, to precisely obtain the user-needed meaningful part of a mesh is a challenging issue. In this paper, we introduce a novel mesh cutout system to efficiently extract meaningful object from a triangular mesh. The algorithm in the current study extends previous min-cut based image segmentation techniques to the domain of 3D mesh. We provide a novel screen-space user interface that allows the user to indicate the meaningful object easily. The results show that our proposed method is relatively simple and effective as a powerful tool for mesh cutout.