A novel parameter learning method of virtual garment

  • Authors:

  • Chen Yujun;Wang Jiaxin;Yang Zehong;Song Yixu

  • Affiliations:

  • State Key Laboratory of Intelligent Technology and System, Computer Science and Technology Department, Tsinghua University, Beijing, China;State Key Laboratory of Intelligent Technology and System, Computer Science and Technology Department, Tsinghua University, Beijing, China;State Key Laboratory of Intelligent Technology and System, Computer Science and Technology Department, Tsinghua University, Beijing, China;State Key Laboratory of Intelligent Technology and System, Computer Science and Technology Department, Tsinghua University, Beijing, China

  • Venue:
  • VSMM'06 Proceedings of the 12th international conference on Interactive Technologies and Sociotechnical Systems
  • Year:
  • 2006

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Abstract

In this paper we present a novel parameter learning and identification method of virtual garment. We innovate in the ordinary parameter identification process and introduce the fabric data (Kawabata Evaluation System data) to combine the expert’s knowledge with fuzzy system. With our method the parameters of virtual garment can be calculated automatically which are assigned by the animator’s experience and hard to tune in the past years. The statistic analysis and machine learning method are used to build the fuzzy system to present the fabric expert’s knowledge. With interactively inputting the human subjective variables to our method, the animator who knows little knowledge in physical attributes of fabric material can also create and tune the virtual garment application. The experimental results indicate that this method can be used in practical virtual environments and has the expansibility to other applications.