Browse > Article
http://dx.doi.org/10.5391/IJFIS.2014.14.2.84

Three-Dimensional Face Point Cloud Smoothing Based on Modified Anisotropic Diffusion Method  

Wibowo, Suryo Adhi (Department of Electrical Engineering, Pusan National University)
Kim, Sungshin (Department of Electrical Engineering, Pusan National University)
Publication Information
International Journal of Fuzzy Logic and Intelligent Systems / v.14, no.2, 2014 , pp. 84-90 More about this Journal
Abstract
This paper presents the results of three-dimensional face point cloud smoothing based on a modified anisotropic diffusion method. The focus of this research was to obtain a 3D face point cloud with a smooth texture and number of vertices equal to the number of vertices input during the smoothing process. Different from other methods, such as using a template D face model, modified anisotropic diffusion only uses basic concepts of convolution and filtering which do not require a complex process. In this research, we used 6D point cloud face data where the first 3D point cloud contained data pertaining to noisy x-, y-, and z-coordinate information, and the other 3D point cloud contained data regarding the red, green, and blue pixel layers as an input system. We used vertex selection to modify the original anisotropic diffusion. The results show that our method has improved performance relative to the original anisotropic diffusion method.
Keywords
Three-dimensional face point cloud; Smoothing; Modified anisotropic diffusion; Selecting vertices;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
연도 인용수 순위
1 J. Weickert, Anisotropic Diffusion in Image Processing, Stuttgart, Germany: B.G. Teubner, 1998. Available http://www.lpi.tel.uva.es/muitic/pim/docus/anisotropic diffusion.pdf
2 S. K. Oh, S. H. Oh, and H. K. Kim, "Design of threedimensional face recognition system using optimized PRBFNNs and PCA: comparative analysis of evolutionary algorithms," Journal of Korean Institute of Intelligent Systems, vol. 23, no. 6, pp. 539-544, Dec. 2013. http://dx.doi.org/10.5391/JKIIS.2013.23.6.539   과학기술학회마을   DOI   ScienceOn
3 G. Taubin, "Linear anisotropic mesh filtering," IBM Research Report RC-22213. Available http://mesh.brown.edu/taubin/pdfs/Taubin-ibm22213.pdf
4 T. Tasdizen, R. Whitaker, P. Burchard, and S. Osher, "Geometric surface smoothing via anisotropic diffusion of normals," in Proceedings of the IEEE Visualization, Boston, MA, November 1, 2002, pp. 125-132. http://dx.doi.org/10.1109/VISUAL.2002.1183766   DOI
5 D. Lopez, "Anisotropic diffusion (Perona & Nalik)," Available http://www. mathworks.com/matlabcentral/fileexchange/14995-anisotropic-diffusion-perona-malik-
6 S. H. Choi, S. Cho, and S. T. Chung, "Improvement of face recognition speed using pose estimation," Journal of Korean Institute of Intelligent Systems, vol. 20, no. 5, pp. 677-682, Oct. 2010. http://dx.doi.org/10.5391/JKIIS.2010.20.5.677   과학기술학회마을   DOI   ScienceOn
7 Y. L. Chen, H. T. Wu, F. Shi, X. Tong, and J. Chai, "Accurate and robust 3D facial capture using a single RGBD camera," in Proceedings of the IEEE International Conference on Computer Vision, Sydney, Australia, December 1-8, 2013, pp. 3615-3622. http://dx.doi.org/10.1109/ICCV.2013.449   DOI
8 H. Yagou, Y. Ohtake, and A. Belyaev, "Mesh smoothing via mean and median filtering applied to face normals," in Proceedings of the Geometric Modeling and Processing, Wako, Japan, July 10-12, 2002, pp. 124-131. http://dx.doi.org/10.1109/GMAP.2002.1027503   DOI
9 C. M. Ma, S. H. Yoo, and S. K. Oh, "Design of face recognition algorithm based optimized pRBFNNs using three-dimensional scanner," Journal of Korean Institute of Intelligent Systems, vol. 22, no. 6, pp. 748-753, Dec. 2012. http://dx.doi.org/10.5391/JKIIS.2012.22.6.748   과학기술학회마을   DOI   ScienceOn
10 P. Perona and J. Malik, "Scale-space and edge detection using anisotropic diffusion," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 12, no. 7, pp. 629-639, Jul. 1990. http://dx.doi.org/10.1109/34.56205   DOI   ScienceOn
11 G. Gerig, O. Kubler, R. Kikinis, and F. A. Jolesz, "Nonlinear anisotropic filtering of MRI data," IEEE Transactions on Medical Imaging, vol. 11, no. 2, pp. 221-232, Jun. 1992. http://dx.doi.org/10.1109/42.141646   DOI   ScienceOn
12 B. Y. L. Li, A. S. Mian, W. Liu, and A. Krishna, "Using Kinect for face recognition under varying poses, expressions, illumination and disguise," in IEEE Workshop on Applications of Computer Vision, Tampa, FL, January 15-17, 2013, pp. 186-192. http://dx.doi.org/10.1109/WACV.2013.6475017   DOI
13 H. Jang, H. Ko, Y. Choi, Y. Han, and H. Hahn, "A new face tracking method using block difference image and Kalman filter in moving picture," Journal of Korean Institute of Intelligent Systems, vol. 15, no. 2, pp. 163-172, Apr. 2005   과학기술학회마을   DOI   ScienceOn
14 A. Mian, M. Bennamoun, and R. Owens, "Automatic 3D face detection, normalization and recognition," in Proceedings of the 3rd International Symposium on 3D Data Processing, Visualization, and Transmission, Chapel Hill, NC, June 14-16, 2006, pp. 735-742. http://dx.doi.org/10.1109/3DPVT.2006.32   DOI
15 V. Blanz and T. Vetter, "Face recognition based on fitting a 3D morphable model," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no. 9, pp. 1063-1074, Sep. 2003. http://dx.doi.org/10.1109/TPAMI.2003.1227983   DOI   ScienceOn
16 B. Y. L. Li, W. Liu, S. An, and A. Krishna, "Tensor based robust color face recognition," in Proceedings of the 21st International Conference on Pattern Recognition, Tsukuba, Japan, November 11-15, 2012, pp. 1719-1722.
17 T. R. Jones, "Feature preserving smoothing of 3D surface scans," M.S. thesis, Massachusetts Institute of Technology, Cambridge, MA, 2003.