关键词: 超混沌, 加密, 三维, 网格模型

Abstract: Data-driven supervised co-segmentation can achieve more accurate segmentation and labeling requirements based on prior knowledge. However, most of supervised methods are extremely time-consuming and difficult to scale up to large data set. The fast 3D shape segmentation and labeling learning method via extreme learning machine is provided, which trains facets and edges simultaneously. Based on that, graph-cut is adopted to smooth and optimize the segmentation boundaries.  The experimental results show that this method can learn quickly and achieve high segmentation accuracy and visual effect in the process of 3D shape segmentation and labeling.

Key words: hyperchaotic, encryption, three-dimensional, mesh model