| 人体表面点云数据的拓扑特征检测与自动分割 |
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| 引用本文： | 吕方梅,习俊通,马登哲. 人体表面点云数据的拓扑特征检测与自动分割[J]. 计算机工程与应用, 2008, 44(6): 196-198. DOI: 10.3778/j.issn.1002-8331.2008.06.059 |
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| 作者姓名： | 吕方梅 习俊通 马登哲 |
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| 作者单位： | 1.上海交通大学 机械与动力工程学院，上海 200030 2.上海理工大学 机械工程学院，上海 200093 |
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| 基金项目： | 上海市信息化专项资金项目，上海理工大学校青年基金项目。 |
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| 摘 要： | 对标准站立测量姿态下的人体表面点云数据的拓扑特征检测与自动分割进行了研究，提出基于全景深度图像表示的人体点云表面拓扑特征检测和自动分割新方法。首先把人体表面的点云数据转换为圆柱极坐标形式，获得人体扫描表面的全景深度图像表示，根据全景深度图像中的层次信息自动检测人体表面的拓扑特征，并根据拓扑特征把人体分割成5个功能结构。实验证明这种方法改进了人体表面点云数据的拓扑特征检测和自动分割的效率和精度。
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| 关 键 词： | 点云 人体表面 全景深度图像 自动分割 |
| 文章编号： | 1002-8331（2008）06-0196-03 |
| 收稿时间： | 2007-08-30 |
| 修稿时间： | 2007-11-15 |
Topological features detection and automatic segmentation of point clouds from human body surface |
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| LV Fang-mei,XI Jun-tong,MA Deng-zhe. Topological features detection and automatic segmentation of point clouds from human body surface[J]. Computer Engineering and Applications, 2008, 44(6): 196-198. DOI: 10.3778/j.issn.1002-8331.2008.06.059 |
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| Authors: | LV Fang-mei XI Jun-tong MA Deng-zhe |
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| Affiliation: | 1.School of Mechanical Engineering，Shanghai Jiaotong University，Shanghai 200030，China 2.College of Mechanical Engineering，University of Shanghai for Science and Technology，Shanghai 200093，China |
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| Abstract: | Topological features detection and automatic segmentation of the point clouds from human body surface in standard standing measuring posture are studied,and a new method based on panoramic range image is proposed which is used for topological features detection and automatic segmentation of the point clouds from human body surface.Point clouds from human body surface are first converted into cylindrical polar coordinates and the panoramic range image of human body is created.Several key landmarks on human surface are detected automatively according to the layer distribution of the panoramic range image.Human scans are segmented into five functional parts in terms of the human key landmarks detected.The experimental results show that the method can improve the efficiency and accuracy of the topological features detection and automatic segmentation of the point clouds from human body surface in standard standing measuring posture. |
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| Keywords: | point clouds human body surface panoramic range image automatic segmentation |
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