International Journal of Fuzzy Logic and Intelligent Systems

  • 제14권2호
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  • Pages.84-90
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  • 2014
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  • 1598-2645(pISSN)
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  • 2093-744X(eISSN)
한국지능시스템학회 (Korean Institute of Intelligent Systems)
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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)
  • 투고 : 2014.06.02
  • 심사 : 2014.06.24
  • 발행 : 2014.06.25
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초록

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.

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참고문헌

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피인용 문헌

  1. Implicit Surface Representation of Three-Dimensional Face from Kinect Sensor vol.25, pp.4, 2015, https://doi.org/10.5391/JKIIS.2015.25.4.412
  2. Convolutional Shallow Features for Performance Improvement of Histogram of Oriented Gradients in Visual Object Tracking vol.2017, pp.1563-5147, 2017, https://doi.org/10.1155/2017/6329864