随机光照双目立体测量系统中的若干关键问题研究
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摘要
物体表面轮廓的三维点云测量在航空航天、车辆船舶、机械制造、生物医学、文物考古、游戏娱乐等领域有着广泛的应用需求。随着现代工业和科学技术的发展，各行业对三维点云测量技术的测量精度、测量效率、数据质量、自动化及稳定性等性能要求日益提高，而如何提高三维点云测量技术的测量性能以满足这些行业的需求是当前迫切需要解决的问题。本文以提高基于随机光照的双目立体测量系统性能为目标，对基于图像的三维点云测量中的自身遮挡、被测物体表面高光反射、三维重建的全过程快速自动处理、多视角测量数据的自拼合等难点问题开展深入研究，主要内容与贡献包括：
1、提出并实现了随机散斑纹理图像的立体点对高效自动匹配方法。结合特征匹配技术和区域匹配技术，提出了一个自动化的特征提取和稳健匹配算法，获取一定数量的匹配点对，作为后续基于区域生长的稠密匹配起始点，从而一方面解决了整个匹配过程的自动化问题，另一方面解决了图像上散斑纹理不连续区域的匹配生长问题。另外，针对随机散斑纹理图像上稠密点对匹配效率较低的问题，采用基于GPU的高效并行加速技术，有效提高了基于区域生长的立体点对匹配效率。
2、针对三维点云测量结果中边缘和棱边等细节的点云生成效果不理想问题，深入研究了图像稠密点对的亚像素匹配技术，并提出了相应的匹配算法。在边缘点对匹配算法中，为避免因背景点像素灰度干扰而引起的匹配点错位，提出了一种自适应变形窗口的相关匹配算法，在一定程度上提高了亚像素匹配精度，同时通过散斑点的区域约束，有效排除了位于背景区域的误匹配点，提高了算法的鲁棒性，改善了被测物体边缘的三维重建效果。在棱边等细节匹配方面，首先采用经典相关匹配方法对随机纹理图像进行快速匹配，初步获取物体表面点云数据，然后基于这些重建数据进行曲面曲率分析，据此对细节区域上的匹配点再次采用改进的相关匹配方法进行匹配，从而提高了亚像素匹配精度，更好地重建了物体表面的细节特征。
3、针对随机光照双目立体测量中的自身遮挡和高光反射问题，提出了单/双目结合的三维轮廓点云测量方法。该方法采用双目立体结构重建两个摄像机的公共区域，同时由单摄像机-投影器构成的两个单目测量单元，对双目测量结果中出现的缺失区域进行填补，使测量结果更加完整，有效避免了由于单个摄像机视线方向存在遮挡或高光等原因引起的三维测量数据缺失。提出的随机光场投射器的投射光线标定方法，其过程简便易行，不需实际确定投影中心的具体位置，且精度不受投影镜头畸变的影响。通过对单/双目测量单元各自产生的数据集中的重叠对应点进行查找和融合，自动生成一个无冗余的三维数据点集。
4、提出了借助微小型姿态传感器进行多视角测量数据拼合的新方法。将一个微小型姿态传感器固定于测量设备上，首先提出了姿态传感器与测量传感器相对安装姿态（旋转变换）的标定方法。每次测量过程中，利用标定结果和姿态传感器实时输出的自身姿态参数，实时解算测量传感器的自身旋转变换，并对该次测取的点云数据进行相应的旋转变换；然后基于数据集重叠区域处数据点法矢方向相同原理，采用聚类方法稳定获取不同视角下测量数据的平移变换，从而实现多视角测量数据拼合。实验表明，这种新方法简便易行、实时在线、稳定可靠，可以很好地用于多视角测量之间数据粗拼合的自动实现。
5、结合多视图几何理论框架下的多站位相机自定位技术与双目立体测量技术，提出了一种多视角点云测量数据自拼合的新方法。该方法不借助任何辅助手段，首先提取两个不同测量视角下左、右相机拍摄的4幅自然纹理图像上的特征点，建立两两图像之间的特征匹配集；然后根据双目立体结构的内在属性，联立两次测量中4幅图像之间的有效匹配约束，采用多视几何理论自动解算两个测量视角的相对位姿。该方法首次将多视图几何求解理论用于双目立体多视角测量数据拼合问题，不仅松弛了测量数据的可拼合条件，有助于测量效率，而且由于充分利用了尽可能多的冗余约束参与拼合问题的求解，提高了算法的鲁棒性，且能获得更高的拼合精度。
本文提出的算法均进行了对比分析和实例验证，且大部分已经应用于自主研发的ReCreator三维测量系统。
Three-dimensional (3D) shape measurement of real-world objects has been widespread applied inthe fields of aerospace, vehicle navigation, machinery manufacturing, biomedicine, heritagepreservation, gaming and entertainment, etc. With the modern industrial and scientific technologicaldevelopment, the requirements of3D point cloud measurement technology for measurement precision,measurement efficiency, data quality, measurement automation and stability are increasing. But howto improve the performance of3D point cloud measurement to meet the increasing requirements hasbecome a critical problem that needs to be addressed. The research in this thesis aims to improve themeasurement performance of binocular stereo measurement system based on random illumination.Several key issues in3D point cloud measurement based on images are further studied in this paper,including self-occlusion, local highlight effect, high-speed automatic3D reconstruction, automaticregistration of multiple range images, etc. The main contents and contributions are as follows.
A stereo matching algorithm with high-efficiency and automation is put forward for the speckleimages. By combining the feature matching and area matching methods, an algorithm for automaticfeature extraction and stable feature matching is proposed to collect a number of pointcorrespondences. These correspondences are taken as the seeds of dense point matching propagatingprocedure, so it can not only solve the automatic implementation of the whole matching process, butalso effectively avoid point absence in discontinuous regions. Besides, the parallel accelerationtechnology based on GPU is adopted to rapidly obtain dense image point correspondences in thematching propagating procedure.
The sub-pixel matching methods of dense image point correspondences are deeply studied. Twomatching algorithms are respectively proposed to improve the quality of the measurement data inedge and minutia regions. In the edge point matching algorithm, to alleviate the matching error causedby the intensity disturbance of background, a correlation matching algorithm with adaptive deformedwindow is put forward to improve the sub-pixel matching precision. The speckle area constraint isimposed to filter out false correspondences located in the background region, which improves therobustness of the algorithm and the quality of the reconstructed edge points. In the minutia matchingalgorithm, the classical correlation matching algorithm is first adopted to rapidly obtain3D pointclouds on the object’s surface. Then according to the curvature properties of these reconstructedpoints, the improved correlation matching algorithm is applied in minutia regions again. Therefore, it improves the sub-pixel matching accuracy, and better reconstructs detail features on object’s surface.
To alleviate the effect of self-occlusion and local highlight of the random-illumination-basedbinocular stereo measurement system, a novel3D shape measurement method is proposed withmonocular/binocular measurement modes. In this method, binocular stereo structure is utilized toreconstruct the common field of view of the two cameras, and the unreconstructed area (data absence)is filled up by two monocular measurement units, which are composed of one single camera and therandom pattern projector. The binocular measurement unit and the two monocular measurement unitsworking together can make the measurement results more integrated and effectively avoid pointabsence caused by the highlight and occlusion in any single camera’s view. A simple and effectivecalibration method is presented to locate the projected rays of the random pattern projection. It isunnecessary to determine the projection center or calibrate the distortion of projector lens, since thesystem precision is not affected by these issues. By searching and integrating the overlapped pointsbetween the three measurement datasets obtained in the binocular and monocular units respectively,the3D measurement data output in one measurement has no redundancy.
A novel scheme for in-process registering multi-view scans with the aid of a miniature attitudesensor has been presented. Since the attitude sensor is fixed on the scanner during the measurementprocess, a simple yet effective algorithm is proposed for calibrating the relative attitudes (rotationtransformation) between the attitude sensor and the scanner. When the scanner is moved from onestandpoint to another in a measuring process, both the calibration results and the real-time readings ofthe attitude sensor are utilized to compute the rotation movement of the scanner. After applying therotation transformation to the current point dataset, the translation movement is efficiently determinedby exploiting the normal vector constraint between the correspondence points. Experimentsdemonstrate that the proposed registration can be done in-process with convenience and stability, andthe rigid transformation obtained can serve as a qualified initial estimate for further fine registration.
By introducing multi-view geometry theory to binocular stereo measurement technology for thefirst time, a novel algorithm is proposed for automatically registering the measurement data takenfrom two orientations by a stereo sensor, without any instrument for assistance. The pointcorrespondences between two of the four natural intensity images, which are captured by the left andright cameras in the two orientations, are first obtained. Then the calibrated parameters of thebinocular stereo structure, together with the effective matching constraints between the four images,are utilized to calculate the relative pose of the stereo sensor based on the multi-view geometry theory.The proposed algorithm not only looses the registration condition, which is helpful to improve the measurement efficiency, but also improves the registration accuracy and robustness since itincorporates as much constraints as possible in the algorithm.
The proposed algorithms have all been fully comparative analyzed and experimental verified, andmost of them have been applied in the ReCreator measurement system developed in our lab.
1、提出并实现了随机散斑纹理图像的立体点对高效自动匹配方法。结合特征匹配技术和区域匹配技术，提出了一个自动化的特征提取和稳健匹配算法，获取一定数量的匹配点对，作为后续基于区域生长的稠密匹配起始点，从而一方面解决了整个匹配过程的自动化问题，另一方面解决了图像上散斑纹理不连续区域的匹配生长问题。另外，针对随机散斑纹理图像上稠密点对匹配效率较低的问题，采用基于GPU的高效并行加速技术，有效提高了基于区域生长的立体点对匹配效率。
2、针对三维点云测量结果中边缘和棱边等细节的点云生成效果不理想问题，深入研究了图像稠密点对的亚像素匹配技术，并提出了相应的匹配算法。在边缘点对匹配算法中，为避免因背景点像素灰度干扰而引起的匹配点错位，提出了一种自适应变形窗口的相关匹配算法，在一定程度上提高了亚像素匹配精度，同时通过散斑点的区域约束，有效排除了位于背景区域的误匹配点，提高了算法的鲁棒性，改善了被测物体边缘的三维重建效果。在棱边等细节匹配方面，首先采用经典相关匹配方法对随机纹理图像进行快速匹配，初步获取物体表面点云数据，然后基于这些重建数据进行曲面曲率分析，据此对细节区域上的匹配点再次采用改进的相关匹配方法进行匹配，从而提高了亚像素匹配精度，更好地重建了物体表面的细节特征。
3、针对随机光照双目立体测量中的自身遮挡和高光反射问题，提出了单/双目结合的三维轮廓点云测量方法。该方法采用双目立体结构重建两个摄像机的公共区域，同时由单摄像机-投影器构成的两个单目测量单元，对双目测量结果中出现的缺失区域进行填补，使测量结果更加完整，有效避免了由于单个摄像机视线方向存在遮挡或高光等原因引起的三维测量数据缺失。提出的随机光场投射器的投射光线标定方法，其过程简便易行，不需实际确定投影中心的具体位置，且精度不受投影镜头畸变的影响。通过对单/双目测量单元各自产生的数据集中的重叠对应点进行查找和融合，自动生成一个无冗余的三维数据点集。
4、提出了借助微小型姿态传感器进行多视角测量数据拼合的新方法。将一个微小型姿态传感器固定于测量设备上，首先提出了姿态传感器与测量传感器相对安装姿态（旋转变换）的标定方法。每次测量过程中，利用标定结果和姿态传感器实时输出的自身姿态参数，实时解算测量传感器的自身旋转变换，并对该次测取的点云数据进行相应的旋转变换；然后基于数据集重叠区域处数据点法矢方向相同原理，采用聚类方法稳定获取不同视角下测量数据的平移变换，从而实现多视角测量数据拼合。实验表明，这种新方法简便易行、实时在线、稳定可靠，可以很好地用于多视角测量之间数据粗拼合的自动实现。
5、结合多视图几何理论框架下的多站位相机自定位技术与双目立体测量技术，提出了一种多视角点云测量数据自拼合的新方法。该方法不借助任何辅助手段，首先提取两个不同测量视角下左、右相机拍摄的4幅自然纹理图像上的特征点，建立两两图像之间的特征匹配集；然后根据双目立体结构的内在属性，联立两次测量中4幅图像之间的有效匹配约束，采用多视几何理论自动解算两个测量视角的相对位姿。该方法首次将多视图几何求解理论用于双目立体多视角测量数据拼合问题，不仅松弛了测量数据的可拼合条件，有助于测量效率，而且由于充分利用了尽可能多的冗余约束参与拼合问题的求解，提高了算法的鲁棒性，且能获得更高的拼合精度。
本文提出的算法均进行了对比分析和实例验证，且大部分已经应用于自主研发的ReCreator三维测量系统。
Three-dimensional (3D) shape measurement of real-world objects has been widespread applied inthe fields of aerospace, vehicle navigation, machinery manufacturing, biomedicine, heritagepreservation, gaming and entertainment, etc. With the modern industrial and scientific technologicaldevelopment, the requirements of3D point cloud measurement technology for measurement precision,measurement efficiency, data quality, measurement automation and stability are increasing. But howto improve the performance of3D point cloud measurement to meet the increasing requirements hasbecome a critical problem that needs to be addressed. The research in this thesis aims to improve themeasurement performance of binocular stereo measurement system based on random illumination.Several key issues in3D point cloud measurement based on images are further studied in this paper,including self-occlusion, local highlight effect, high-speed automatic3D reconstruction, automaticregistration of multiple range images, etc. The main contents and contributions are as follows.
A stereo matching algorithm with high-efficiency and automation is put forward for the speckleimages. By combining the feature matching and area matching methods, an algorithm for automaticfeature extraction and stable feature matching is proposed to collect a number of pointcorrespondences. These correspondences are taken as the seeds of dense point matching propagatingprocedure, so it can not only solve the automatic implementation of the whole matching process, butalso effectively avoid point absence in discontinuous regions. Besides, the parallel accelerationtechnology based on GPU is adopted to rapidly obtain dense image point correspondences in thematching propagating procedure.
The sub-pixel matching methods of dense image point correspondences are deeply studied. Twomatching algorithms are respectively proposed to improve the quality of the measurement data inedge and minutia regions. In the edge point matching algorithm, to alleviate the matching error causedby the intensity disturbance of background, a correlation matching algorithm with adaptive deformedwindow is put forward to improve the sub-pixel matching precision. The speckle area constraint isimposed to filter out false correspondences located in the background region, which improves therobustness of the algorithm and the quality of the reconstructed edge points. In the minutia matchingalgorithm, the classical correlation matching algorithm is first adopted to rapidly obtain3D pointclouds on the object’s surface. Then according to the curvature properties of these reconstructedpoints, the improved correlation matching algorithm is applied in minutia regions again. Therefore, it improves the sub-pixel matching accuracy, and better reconstructs detail features on object’s surface.
To alleviate the effect of self-occlusion and local highlight of the random-illumination-basedbinocular stereo measurement system, a novel3D shape measurement method is proposed withmonocular/binocular measurement modes. In this method, binocular stereo structure is utilized toreconstruct the common field of view of the two cameras, and the unreconstructed area (data absence)is filled up by two monocular measurement units, which are composed of one single camera and therandom pattern projector. The binocular measurement unit and the two monocular measurement unitsworking together can make the measurement results more integrated and effectively avoid pointabsence caused by the highlight and occlusion in any single camera’s view. A simple and effectivecalibration method is presented to locate the projected rays of the random pattern projection. It isunnecessary to determine the projection center or calibrate the distortion of projector lens, since thesystem precision is not affected by these issues. By searching and integrating the overlapped pointsbetween the three measurement datasets obtained in the binocular and monocular units respectively,the3D measurement data output in one measurement has no redundancy.
A novel scheme for in-process registering multi-view scans with the aid of a miniature attitudesensor has been presented. Since the attitude sensor is fixed on the scanner during the measurementprocess, a simple yet effective algorithm is proposed for calibrating the relative attitudes (rotationtransformation) between the attitude sensor and the scanner. When the scanner is moved from onestandpoint to another in a measuring process, both the calibration results and the real-time readings ofthe attitude sensor are utilized to compute the rotation movement of the scanner. After applying therotation transformation to the current point dataset, the translation movement is efficiently determinedby exploiting the normal vector constraint between the correspondence points. Experimentsdemonstrate that the proposed registration can be done in-process with convenience and stability, andthe rigid transformation obtained can serve as a qualified initial estimate for further fine registration.
By introducing multi-view geometry theory to binocular stereo measurement technology for thefirst time, a novel algorithm is proposed for automatically registering the measurement data takenfrom two orientations by a stereo sensor, without any instrument for assistance. The pointcorrespondences between two of the four natural intensity images, which are captured by the left andright cameras in the two orientations, are first obtained. Then the calibrated parameters of thebinocular stereo structure, together with the effective matching constraints between the four images,are utilized to calculate the relative pose of the stereo sensor based on the multi-view geometry theory.The proposed algorithm not only looses the registration condition, which is helpful to improve the measurement efficiency, but also improves the registration accuracy and robustness since itincorporates as much constraints as possible in the algorithm.
The proposed algorithms have all been fully comparative analyzed and experimental verified, andmost of them have been applied in the ReCreator measurement system developed in our lab.
引文
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