Virtual Reality

, Volume 20, Issue 3, pp 159–172 | Cite as

Optimizing human model reconstruction from RGB-D images based on skin detection

  • Guang Chen
  • Jituo Li
  • Jiping Zeng
  • Bei Wang
  • Guodong Lu
Original Article

Abstract

This paper reconstructs human model from multi-view RGB-D images of an Xbox One Kinect. We preprocess the depth images by implicit surface de-noising and then part-wisely register them into a point cloud. A template model is selected from the human model database to fit the registered point cloud of a human body by Laplacian deformation. Skin detection of RGB-D images helps to tightly constrain the skin parts of human body in template fitting step in order to get more precise and lifelike human model. We propose a robust skin detection method that is not affected by clothing pattern and background. Experiments demonstrate the effectiveness of our method.

Keywords

Human model reconstruction Kinect RGB-D image Skin detection 

Notes

Acknowledgments

This work was partially supported by National Natural Science Foundation of China (51575481, 61379096) and Project of Public Technology Research in Industry of Zhejiang Province (2014C31048).

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Copyright information

© Springer-Verlag London 2016

Authors and Affiliations

  • Guang Chen
    • 1
  • Jituo Li
    • 1
  • Jiping Zeng
    • 1
  • Bei Wang
    • 1
  • Guodong Lu
    • 1
  1. 1.Research Center of Design and Production Innovation, College of Mechanical EngineeringZhejiang UniversityHangzhouPeople’s Republic of China

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