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21. 发明申请

US20100166294A1 SYSTEM AND METHOD FOR THREE-DIMENSIONAL ALIGNMENT OF OBJECTS USING MACHINE VISION 有权
标题翻译：使用机器视觉的三维对准对象的系统和方法
公开(公告)号：US20100166294A1
公开(公告)日：2010-07-01
申请号：US12345130
申请日：2008-12-29
申请人： Cyril C. Marrion , Nigel J. Foster , Lifeng Liu , David Y. Li , Guruprasad Shivaram , Aaron S. Wallack , Xiangyun Ye
发明人： Cyril C. Marrion , Nigel J. Foster , Lifeng Liu , David Y. Li , Guruprasad Shivaram , Aaron S. Wallack , Xiangyun Ye
IPC分类号： G06K9/00
CPC分类号： G06K9/00214 , G06K9/6211
摘要： This invention provides a system and method for determining the three-dimensional alignment of a modeledobject or scene. After calibration, a 3D (stereo) sensor system views the object to derive a runtime 3D representation of the scene containing the object. Rectified images from each stereo head are preprocessed to enhance their edge features. A stereo matching process is then performed on at least two (a pair) of the rectified preprocessed images at a time by locating a predetermined feature on a first image and then locating the same feature in the other image. 3D points are computed for each pair of cameras to derive a 3D point cloud. The 3D point cloud is generated by transforming the 3D points of each camera pair into the world 3D space from the world calibration. The amount of 3D data from the point cloud is reduced by extracting higher-level geometric shapes (HLGS), such as line segments. Found HLGS from runtime are corresponded to HLGS on the model to produce candidate 3D poses. A coarse scoring process prunes the number of poses. The remaining candidate poses are then subjected to a further more-refined scoring process. These surviving candidate poses are then verified by, for example, fitting found 3D or 2D points of the candidate poses to a larger set of corresponding three-dimensional or two-dimensional model points, whereby the closest match is the best refined three-dimensional pose.
摘要翻译：本发明提供一种用于确定建模对象或场景的三维对准的系统和方法。校准后，3D（立体声）传感器系统会查看对象以导出包含对象的场景的运行时3D表示。来自每个立体声头的整流图像被预处理以增强其边缘特征。然后，通过在第一图像上定位预定特征，然后将另一图像中的相同特征定位，对至少两（一对）经整流的预处理图像执行立体匹配处理。为每对相机计算3D点以导出3D点云。 3D点云是通过将世界三维空间中的每个摄像机对的3D点变换为世界校准而产生的。通过提取诸如线段的较高级几何形状（HLGS）来减少来自点云的3D数据量。从运行时发现的HLGS对应于模型上的HLGS，以产生候选的3D姿势。粗略的评分过程会减少姿势的数量。然后，剩下的候选姿势进一步进行更精细的评分过程。然后通过例如将候选姿势的3D或2D点拟合到较大的一组相应的三维或二维模型点来验证这些幸存的候选姿势，由此最接近的匹配是最佳精细三维姿态。

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