三维重建应用系统研究
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摘要
物体三维重建是指对三维物体建立适合计算机表示和处理的数学模型,是在计算机环境下对其进行处理、操作和分析其性质的基础,也是在计算机中建立表达客观世界的虚拟现实的关键技术。因此,物体三维重建是计算机辅助几何设计(CAGD)、计算机图形学(CG)、计算机动画、计算机视觉、医学图像处理、科学计算和虚拟现实、数字媒体创作等领域的共性科学问题和核心技术。
在计算机内生成物体三维表示主要有两类方法。一类是使用几何建模软件通过人机交互生成人为控制下的物体三维几何模型,另一类是通过一定的手段获取真实物体的几何形状。前者实现技术已经十分成熟,现有若干软件支持,比如:3DSMAX、Maya、AutoCAD、UG等等,它们一般使用具有数学表达式的曲线曲面表示几何形状。后者一般称为三维重建过程,三维重建是指利用二维投影恢复物体三维信息(形状等)的数学过程和计算机技术,包括数据获取、预处理、点云拼接和特征分析等步骤。本文建立了一套独立的以三维重建为核心的应用系统,实现了基于三维扫描的建模模块、三维碎片拼接模块、三维人脸识别模块以及基于二维编辑的三维造型后处理功能;同时将基于鱼眼镜头的双目视觉算法与三维重建进行了融合。其中三维建模和三维点云数据特征分析是至关重要的部分,也是本文研究的重点内容。
本文的工作以国家自然科学基金课题“基于海量数据点的三维表示中的关键问题研究”、山东自然科学基金课题“海量数据处理中的高精度三维表示问题研究”等重点课题为依托,讨论了这个领域中的一系列关键问题。这些问题包括:三维扫描过程分析、三维面片数据拼接、空间点云几何不变量研究、双目视觉与全景技术融合进行三维重建以及基于二维编辑的三维造型技术等。具体说来,主要贡献包括以下几点:
(1)实现了基于白光结构光栅的非接触式三维扫描仪,为三维重建和后续工作提供了丰富和精确的数据。普通镜头存在多种几何畸变,严重影响实验数据的获取;而边缘检测的策略也直接影响到了深度数据的精确性。在这个阶段的工作中主要提出了迭代式镜头几何校正算法、结构光栅图像亚像素精度边缘检测算法,并实现了空间散乱点云数据的面片可视化。
(2)提出了一种基于导数动态时间规整(DDTW)的三维碎片自动拼接方法,可以计算两块碎片之间最优的拼接方式。同时设计了一种基于抗噪区间拟合的挠率估计方法和常数时间复杂度的三维重叠检测方法,大幅度提高了拼接的速度和准确性。首先确定物体碎片的轮廓曲线,查找角点,根据角点将轮廓曲线分段成子轮廓线,计算子轮廓曲线的挠率特征串;然后使用DDTW对两个特征串进行匹配,并给出匹配度的度量值,继而根据对应点的空间位置关系对碎片进行放缩和刚体变换,调用三维重叠检测方法排除重叠匹配;最后根据给定的评价标准找到最优匹配作为最终拼接结果。实验表明,该方法实现简单,鲁棒性强,能快速得到三维碎片集合的拼接结果。
(3)对三维空间点云数据进行几何特征分析,找到了人脸表情无关的几何特征不变量。使得人脸在不同表情下扫描获得的空间数据最终能够表示为统一的形式,很大程度上排除了表情对人脸三维空间数据表示的影响,建立了三维人脸数据库,实现了基于三维扫描表情无关的人脸识别系统,为身份验证和安全保障工作提供了新的思路和方式。
(4)研究了全景图自动拼接的方式方法,提出了基于图像变形的图像自动匹配算法,实现了基于鱼眼镜头和数码相机多幅图像的自动拼接,获得了竖直视角180度、水平视角360度的全景浏览。在此基础上改变全景拍摄高度,可以获得在不同拍摄点对同一场景拍摄的不同视角的全景图片。利用双目视觉的有关原理,以多视角全景图为数据,实现了场景三维点云数据场的重建,为现场保留、重现工作提供了强有力的技术支持。这项工作也可以作为三维重建中一个新的分支。
(5)做为三维重建系统的有益补充,本文提出了基于二维图像编辑的三维表面造型方法。利用简单和通用的二维平面编辑操作进行三维表面造型定义,然后建立二维平面坐标系与三维几何体表面区域的映射关系,最终将造型定义展现到三维几何体表面。
3D construction for objects means to create mathematical models for 3D objects which are suitable for computer to represent and process. It is the base for data process, management and analysis in computer environment. It is also the key technology in creating virtual reality to express the external world. So 3D reconstruction for objects is the commom science problem and key technology in many domains, including computer aided geometric design (CAGD), computer graphics (CG), computer animation, computer vision, medical image processing, science calculation, virtual reality and digital media invention, etc.
There are two kinds of approachs to generate 3D representation for objects. One way is to interact with geometric modeling software to generate 3D geometric models for objects according to manual design. The other way is to obtain range data from real objects. The former is more mature, and has rich software support, such as: 3DSMAX, Maya, AutoCAD and UG, etc. They describe objects with curves and surfaces defined by mathematic expressions. Generally, the latter approach is called a 3D reconstruction which means to resume 3D information of objects from their 2D projection images. It involves several function modules, such as data obtaining, data preprocessing, data cloud re-assembly and geometric feature analysis. Our work is to construct a whole 3D reconstruction application system, including 3D modeling module, 3D fragment re-assembly module, 3D face recognition module and 3D shaping module based on 2D editing. Simultaneously, we make a fusion of stereo vision and 3D reconstruction. Among them, the 3D reconstruction and range data point cloud feature-analysis seem to be more important which are addressed in this paper as key points.
In this paper, we organize some research work done with support of "Research on key problems in 3D representation based on mass data" by the National Natural Science Funds and "Research on problems in accurate 3D representation during mass data processing" by the Shandong Province Natural Science Funds. The key research points include: the process analysis of 3D scanning, 3D fragments automatic reassembly, geometry invariant of 3D range point data cloud and the merge of stereo vision and panorama stitching, etc. Specifically, they are listed as follow.
First, a whole structured white light based untouching 3D scanning system is implemented. It and can provide rich and accurate data for 3D reconstruction and other related work. Common lens has greate geometry distortion, which can affect the quality of scan data badly. And the edge detection algorithm will also determine the accuracy of range data. Here, an iterative method is carried out to perform the automatic lens calibration. Then a data-fitting based method is proposed to improve the accuracy of sub-pixel edge detection. Finally, the visualization of the data cloud is given.
Second, we present an automatic re-assembly method for matching 3D fragments, which can compute the best match of a pair of broken pieces. To improve speed and accuracy, we give a torsion estimation method based on anti-noise section and a fixed constant time cost 3D overlapping test method. First, the contour curves of fragments are found, then the corner points. Contour curves are divided into several sub-contours. Second, the torsion sequences are obtained for the DDTW based matching work. Thus, the scale and translation matrixes can be computed to change the size and position of one fragment. Best matching result will be finally chosen according to matching test and extra evaluations. Experiment results show that this method is simple and robust, and can get proper matching results quickly.
Third, the expression ignored invariant of 3D face scan data is discovered during the feature analysis on 3D range data point cloud. This makes it possible that face surface data with different expressions can share a uniform data presentation. This can help to identify human face no matter what expression he makes. Then a 3D human face database is setup and serves a practical face recognition system. These efforts provide new thoughts and fashions to identity recognition and security guarantee applications.
Fourth, an automitic panorama stitching method is carried out. An image transformation based method is proposed to provide automatic stitching for fish-eye panorama pictures. Thus, with a fish-eye lens and a common digital camera, people can get a whole panorama picture easily, which can cover 180 degrees vertically and 360 degrees horizontally. Then the capture position is changed. So a pair of pictures with different view angle is taken. The stereo vision algorithm is also combined in the application to obtain the 3D range data cloud of the scene. This work is very useful for scene reservation and review.This research can also be regarded as a new branch of 3D reconstruction.
Finally, to provide additional ability to manipulate 3D shape, we implement a 3D editing method base on 2D drawing. 3D shape can be defined in 2D domain in simple and general ways, and then create a mapping from 2D domain to 3D domain, thus the shape definition can be presented on the surface of the 3D geometry model as 3D shapes.
在计算机内生成物体三维表示主要有两类方法。一类是使用几何建模软件通过人机交互生成人为控制下的物体三维几何模型,另一类是通过一定的手段获取真实物体的几何形状。前者实现技术已经十分成熟,现有若干软件支持,比如:3DSMAX、Maya、AutoCAD、UG等等,它们一般使用具有数学表达式的曲线曲面表示几何形状。后者一般称为三维重建过程,三维重建是指利用二维投影恢复物体三维信息(形状等)的数学过程和计算机技术,包括数据获取、预处理、点云拼接和特征分析等步骤。本文建立了一套独立的以三维重建为核心的应用系统,实现了基于三维扫描的建模模块、三维碎片拼接模块、三维人脸识别模块以及基于二维编辑的三维造型后处理功能;同时将基于鱼眼镜头的双目视觉算法与三维重建进行了融合。其中三维建模和三维点云数据特征分析是至关重要的部分,也是本文研究的重点内容。
本文的工作以国家自然科学基金课题“基于海量数据点的三维表示中的关键问题研究”、山东自然科学基金课题“海量数据处理中的高精度三维表示问题研究”等重点课题为依托,讨论了这个领域中的一系列关键问题。这些问题包括:三维扫描过程分析、三维面片数据拼接、空间点云几何不变量研究、双目视觉与全景技术融合进行三维重建以及基于二维编辑的三维造型技术等。具体说来,主要贡献包括以下几点:
(1)实现了基于白光结构光栅的非接触式三维扫描仪,为三维重建和后续工作提供了丰富和精确的数据。普通镜头存在多种几何畸变,严重影响实验数据的获取;而边缘检测的策略也直接影响到了深度数据的精确性。在这个阶段的工作中主要提出了迭代式镜头几何校正算法、结构光栅图像亚像素精度边缘检测算法,并实现了空间散乱点云数据的面片可视化。
(2)提出了一种基于导数动态时间规整(DDTW)的三维碎片自动拼接方法,可以计算两块碎片之间最优的拼接方式。同时设计了一种基于抗噪区间拟合的挠率估计方法和常数时间复杂度的三维重叠检测方法,大幅度提高了拼接的速度和准确性。首先确定物体碎片的轮廓曲线,查找角点,根据角点将轮廓曲线分段成子轮廓线,计算子轮廓曲线的挠率特征串;然后使用DDTW对两个特征串进行匹配,并给出匹配度的度量值,继而根据对应点的空间位置关系对碎片进行放缩和刚体变换,调用三维重叠检测方法排除重叠匹配;最后根据给定的评价标准找到最优匹配作为最终拼接结果。实验表明,该方法实现简单,鲁棒性强,能快速得到三维碎片集合的拼接结果。
(3)对三维空间点云数据进行几何特征分析,找到了人脸表情无关的几何特征不变量。使得人脸在不同表情下扫描获得的空间数据最终能够表示为统一的形式,很大程度上排除了表情对人脸三维空间数据表示的影响,建立了三维人脸数据库,实现了基于三维扫描表情无关的人脸识别系统,为身份验证和安全保障工作提供了新的思路和方式。
(4)研究了全景图自动拼接的方式方法,提出了基于图像变形的图像自动匹配算法,实现了基于鱼眼镜头和数码相机多幅图像的自动拼接,获得了竖直视角180度、水平视角360度的全景浏览。在此基础上改变全景拍摄高度,可以获得在不同拍摄点对同一场景拍摄的不同视角的全景图片。利用双目视觉的有关原理,以多视角全景图为数据,实现了场景三维点云数据场的重建,为现场保留、重现工作提供了强有力的技术支持。这项工作也可以作为三维重建中一个新的分支。
(5)做为三维重建系统的有益补充,本文提出了基于二维图像编辑的三维表面造型方法。利用简单和通用的二维平面编辑操作进行三维表面造型定义,然后建立二维平面坐标系与三维几何体表面区域的映射关系,最终将造型定义展现到三维几何体表面。
3D construction for objects means to create mathematical models for 3D objects which are suitable for computer to represent and process. It is the base for data process, management and analysis in computer environment. It is also the key technology in creating virtual reality to express the external world. So 3D reconstruction for objects is the commom science problem and key technology in many domains, including computer aided geometric design (CAGD), computer graphics (CG), computer animation, computer vision, medical image processing, science calculation, virtual reality and digital media invention, etc.
There are two kinds of approachs to generate 3D representation for objects. One way is to interact with geometric modeling software to generate 3D geometric models for objects according to manual design. The other way is to obtain range data from real objects. The former is more mature, and has rich software support, such as: 3DSMAX, Maya, AutoCAD and UG, etc. They describe objects with curves and surfaces defined by mathematic expressions. Generally, the latter approach is called a 3D reconstruction which means to resume 3D information of objects from their 2D projection images. It involves several function modules, such as data obtaining, data preprocessing, data cloud re-assembly and geometric feature analysis. Our work is to construct a whole 3D reconstruction application system, including 3D modeling module, 3D fragment re-assembly module, 3D face recognition module and 3D shaping module based on 2D editing. Simultaneously, we make a fusion of stereo vision and 3D reconstruction. Among them, the 3D reconstruction and range data point cloud feature-analysis seem to be more important which are addressed in this paper as key points.
In this paper, we organize some research work done with support of "Research on key problems in 3D representation based on mass data" by the National Natural Science Funds and "Research on problems in accurate 3D representation during mass data processing" by the Shandong Province Natural Science Funds. The key research points include: the process analysis of 3D scanning, 3D fragments automatic reassembly, geometry invariant of 3D range point data cloud and the merge of stereo vision and panorama stitching, etc. Specifically, they are listed as follow.
First, a whole structured white light based untouching 3D scanning system is implemented. It and can provide rich and accurate data for 3D reconstruction and other related work. Common lens has greate geometry distortion, which can affect the quality of scan data badly. And the edge detection algorithm will also determine the accuracy of range data. Here, an iterative method is carried out to perform the automatic lens calibration. Then a data-fitting based method is proposed to improve the accuracy of sub-pixel edge detection. Finally, the visualization of the data cloud is given.
Second, we present an automatic re-assembly method for matching 3D fragments, which can compute the best match of a pair of broken pieces. To improve speed and accuracy, we give a torsion estimation method based on anti-noise section and a fixed constant time cost 3D overlapping test method. First, the contour curves of fragments are found, then the corner points. Contour curves are divided into several sub-contours. Second, the torsion sequences are obtained for the DDTW based matching work. Thus, the scale and translation matrixes can be computed to change the size and position of one fragment. Best matching result will be finally chosen according to matching test and extra evaluations. Experiment results show that this method is simple and robust, and can get proper matching results quickly.
Third, the expression ignored invariant of 3D face scan data is discovered during the feature analysis on 3D range data point cloud. This makes it possible that face surface data with different expressions can share a uniform data presentation. This can help to identify human face no matter what expression he makes. Then a 3D human face database is setup and serves a practical face recognition system. These efforts provide new thoughts and fashions to identity recognition and security guarantee applications.
Fourth, an automitic panorama stitching method is carried out. An image transformation based method is proposed to provide automatic stitching for fish-eye panorama pictures. Thus, with a fish-eye lens and a common digital camera, people can get a whole panorama picture easily, which can cover 180 degrees vertically and 360 degrees horizontally. Then the capture position is changed. So a pair of pictures with different view angle is taken. The stereo vision algorithm is also combined in the application to obtain the 3D range data cloud of the scene. This work is very useful for scene reservation and review.This research can also be regarded as a new branch of 3D reconstruction.
Finally, to provide additional ability to manipulate 3D shape, we implement a 3D editing method base on 2D drawing. 3D shape can be defined in 2D domain in simple and general ways, and then create a mapping from 2D domain to 3D domain, thus the shape definition can be presented on the surface of the 3D geometry model as 3D shapes.
引文
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