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阶层式三维形状环特征提取方法 被引量:2

Hierarchical three-dimensional shape ring feature extraction method
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摘要 针对已有的三维形状局部特征属性单一及缺乏空间结构信息的问题,提出了一种融合三维形状拓扑连接信息的阶层式特征提取框架,并得到具有平移不变性的三维形状环特征。首先,以三维形状底层特征提取为基础,进一步利用等测地线环的方式对特征点的局部区域进行建模,抽象出包含丰富空间几何结构信息的中层特征;然后,利用稀疏编码方式对中层特征进一步概括抽象,进而得到更具区分力和丰富信息的高层特征。将该高层特征与已有的尺度不变的热核描述子(SI-HKS)在三维形状对应和形状检索这两类任务中进行对比,该特征准确率分别提高了24.5个百分点和7.2个百分点。实验结果表明所提特征相较于已有的特征描述符具有更高的分辨率和识别度。 The existing three-dimensional shape local features are mostly lack of spatial structure information and only contain a single property. In order to solve the problems, a hierarchical feature extraction framework integrating topological connection information of three-dimensional shape was proposed to obtain the three-dimensional shape ring feature with shift invariance. Firstly, based on the low-level feature extraction of a three-dimensional shape, the local region of feature points was modeled by the way of the isometric geodesic ring, which could extract the middle-level feature containing rich spatial geometric structure information. Then, the middle-level feature was further abstracted by using sparse coding to obtain more discriminative high-level feature with abundant information. The obtained high-level feature was compared with the existing Scale Invariant Heat Kernel Signature(SI-HKS) in two tasks of three-dimensional shape correspondence and shape retrieval,and its accuracy was increased by 24. 5 percentage points and 7. 2 percentage points respectively. The experimental results show that the proposed feature has higher resolution and recognition than the existing feature descriptors.
作者 左向梅 贾丽姣 韩鹏程 ZUO Xiangmei 1 , JIA Lijiao 1, HAN Pengcheng 2(1. Experimental Aircraft Design and Modification Institute, Chinese Flight Test Establishment, Xi an Shaanxi 710089, China ;2. School of Aeronautics, Northwestern Polytechnical University, Xi an Shaanxi 710072, Chin)
出处 《计算机应用》 CSCD 北大核心 2018年第6期1755-1759,1764,共6页 journal of Computer Applications
基金 国家自然科学基金资助项目(61573284)~~
关键词 三维形状 局部特征 稀疏编码 拓扑连接 形状检索 three-dimensional shape local feature sparse coding topological connection shape retrieval
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