Abstract
Data Registration is one of the key techniques in 3D scanning. The traditional methods for data registration have some disadvantages which always need many calibration markers or other accessories. Those will greatly reduce the convenience and usability for the scanning systems, and more markers will covered the limited useful surface of the measured object. This paper proposed a new method to overcome these shortcomings. In the method, the 3D scanner and the motion capture device, which have completely different elements, are effectively combined as a whole system. The position and posture of the measured object can be optionally changed as wish. Mocap system guides the spatial localization for the measured object which has a high flexibility and precision. Dynamic motion data and the static scan data can be obtained in real-time by using the Mocap system and 3D scanner, respectively. In the final, heterogeneous spatial data will be converted to a same 3D space, and the parts of point clouds will be spliced to a whole 3D model. The experiments show that the method is valid.
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References
Sun, J.Z., Hu, Y., Ma, Y.Q.: An algorithm generate voronoi diagram based on delaunay triangulation. J. Comput. Appl. 1(01), 75–77 (2010)
Lovato, C., Castellani, U., Zancanaro, C.: Automatic labelling of anatomical landmarks on 3D body scans. Graph. Models 76(6), 648–657 (2014)
Han, F., Duan, X.F.: Research on the point cloud data processing method of 3D terrestrial laser scanning in existing railway track. Appl. Mech. Mater. 744, 1298–1302 (2015)
Liu, M.M., Richard, H., Salzmann, M.: Mirror surface reconstruction from a single image. In: 2015 IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 760–773. IEEE Press (2015)
Zuo, C., Lu, M., Tan, Z.G.: A novel algorithm for registration of point clouds. Chin. J. Lasers 39(12), 211–218 (2012)
Wu, S., Sun, W., Long, P., et al.: Quality-driven poisson-guided autoscanning. ACM Trans. Graph., 33(6) (2014). Article No 203
Amenta, N., Choi, S., Dey, T.: A simple algorithm for homeomorphic surface reconstruction. Int. J. Comput. Geomet. Appl. 12, 125–141 (2002)
Zhou, L.M., Zheng, S.Y., Huang, R.Y.: A registration algorithm for point clouds obtained by scanning objects on turntable. Acta Geodaetica Cartogr. Sin. 42, 73–79 (2013)
Gressin, A., Mallet, C., Demantké, J.: Towards 3D lidar point cloud registration improvement using optimal neighborhood knowledge. ISPRS J. Photogrammetry and Remote Sens. 79, 240–251 (2013)
Yuan, J.Y., Wang, Q., Li, Bailin.: Using multi-view network constraints among reference marker points to realize coarse registration in structured light system with high accuracy. J. Comput. Aided Des. Comput. Graph. 4,014 (2015)
Chen, Y., Medioni, G.: Object modeling by registration of multiple range images. In: 1991 IEEE International Conference on Robotics and Automation, pp. 2724–2729. IEEE Press (1991)
Dai, J.S.: Euler-rodrigues formula variations, quaternion conjugation and intrinsic connections. Mech. Mach. Theory 92, 144–152 (2015)
Zhu, Y.J., Zhou, L., Zhang, L.Y.: Registration of scattered cloud data. J. Comput. Aided Des. Comput. Graph. 18, 475–481 (2006)
Xu, J.T., Sun, Y.W., Liu, W.J.: Optimal localization of free-form shaped parts in precision inspection. Chin. J. Mech. Eng. 43, 175–179 (2007)
Wang, J., Zhou, L.S.: Surface rough matching algorithm based on maximum weight clique. J. Comput. Aided Des. Comput. Graph. 20(2), 167–173 (2008)
Long, X., Zhong, Y.X., Li, R.J.: 3-D surface integration in structured light 3-D scanning. J. Tsinghua Univ. (Sci. Technol.) 42, 477–480 (2002)
Kim, J.Y., Kim, L.S., Hwang, S.H.: An advanced contrast enhancement using partially overlapped sub-block histogram equalization. Circuits Syst. Video Technol. 11, 475–484 (2001)
Cheng, X.J., Wang, F.: Method of calculating sphere surface parameters by measuring several point coordinate on a sphere. Railway Invest. Surveying 32, 1–2 (2007)
Acknowledgement
This work is supported by the National Natural Science Foundation of China (No. 61370141, 61300015), the Program for Liaoning Innovative Research Team in University (Nos. LT2015002), the Program for Science and Technology Research in New Jinzhou District (No. KJCX-ZTPY-2014-0012).
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Zhang, S., Zhou, D., Zhang, Q. (2016). A Method of Data Registration for 3D Point Clouds Combining with Motion Capture Technologies. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, TP. (eds) Intelligent Information and Database Systems. ACIIDS 2016. Lecture Notes in Computer Science(), vol 9621. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49381-6_72
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DOI: https://doi.org/10.1007/978-3-662-49381-6_72
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