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

• Main Authors: Zulkepli, Majid, Setan, Halim, Chong, Albert K.
• Format: Article
• Language: English
• Published: Faculty of Geoinformation Science and Engineering, Universiti Teknologi Malaysia 2009
• Subjects: T Technology (General)
• Online Access: http://eprints.utm.my/id/eprint/11781/1/Zulkepli_Majid2009_AccuracyAssessmentsofPointCloud.pdf; http://eprints.utm.my/id/eprint/11781/; http://www.fksg.utm.my/journal/GSJ/PDF/GSJ%20VOL%209%20NO%202%202009/4%20-%20new%20-%20Accuracy%20Assesment%20of%20Point%203D%20-%20Zulkepli%20Majid2.pdf
• Institution: Universiti Teknologi Malaysia

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