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Accuracy assessments of point cloud 3D registration method for high accuracy craniofacial mapping

机译:高精度颅面贴图的点云3D配准方法精度评估

摘要

Three dimensional (3D) laser scanning technology has found to be an excellent method for modeling and measuring 3D objects. The 3D point clouds of an object can be acquired within less than one second and stored digitally for pre-processing task. Complex mapping of 3D object such as human faces required at least two scanning images to cover the complete facial area (from right ear to left ear, and from hair line to bottom part of the chin) with optimum 3D modeling accuracy. For complete 3D model generation, the scanning images are needed to be registered and merged together. Existing registration method used corresponding features between the two scanned images as registration primitive and finally 3D transformation algorithm was applied to register the images. This paper describes the use of photogrammetric targets, as registration primitive to register two scanning images of human face. The so called “paper targets” were setup on the special design photogrammetric control frame where the human face was placed at the middle of the frame during scanning process. The photogrammetric control frame was calibrated using close-range convergent photogrammetry with coded targets and high precision scale bars to determine the precise 3D coordinate of such targets. The targets were also included in the scanning images and represented as point clouds. Via laser scanning images, the centroid of the targets was precisely measured and the 3D transformation algorithm was successfully applied to transform the scanning point clouds from laser scanning coordinate system to photogrammetric coordinate system. The output of the registered point clouds was displayed and processed in reverse engineering RapidForm 2004 software. The accuracy of the method was evaluated using shell-shell deviation analysis method where the average deviation of the two scanning images was calculated. The results show that the accuracy of the 3D registration accuracy using photogrammetric targets was measured to be 0.129mm to 0.285mm. The reliability of the 3D registration accuracy using photogrammetric targets method was also evaluated and the standard deviation of the method is 0.10mm to 0.50mm
机译:已经发现,三维(3D)激光扫描技术是用于建模和测量3D对象的绝佳方法。可以在不到一秒钟的时间内获取对象的3D点云,并将其数字存储以进行预处理。 3D对象(如人脸)的复杂映射需要至少两个扫描图像才能覆盖整个面部区域(从右耳到左耳,从发际线到下巴的底部),并具有最佳的3D建模精度。对于完整的3D模型生成,需要将扫描图像配准并合并在一起。现有的配准方法使用两个扫描图像之间的对应特征作为配准原语,最后应用3D变换算法对图像进行配准。本文介绍了摄影测量目标的使用,将其作为配准原语来配准两张人脸扫描图像。在特殊设计的摄影测量控制框架上设置了所谓的“纸张目标”,在扫描过程中将人脸放置在框架的中间。使用具有编码目标和高精度比例尺的近距离会聚摄影测量法对摄影测量控制框架进行校准,以确定此类目标的精确3D坐标。目标也包括在扫描图像中,并表示为点云。通过激光扫描图像,可以精确地测量目标的质心,并成功地应用了3D转换算法,将扫描点云从激光扫描坐标系转换为摄影测量坐标系。注册点云的输出在逆向工程RapidForm 2004软件中显示和处理。使用壳-壳偏差分析方法评估该方法的准确性,其中计算两个扫描图像的平均偏差。结果表明,使用摄影测量目标测量的3D配准精度的精度为0.129mm至0.285mm。还评估了使用摄影测量目标法的3D配准精度的可靠性,该方法的标准偏差为0.10mm至0.50mm

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