Earticle

초록

영어

3D motion capture is to track and record human movements. In recent years, it has been applied into many fields, such as human computer interaction, animation, etc. Low-level segmentation of motion capture data is of significance to the various applications of 3D motion capture; however, due to the high dimensionality of motion capture data, traditional low-level segmentation methods can hardly work out a suitable segmentation for motion capture data. In order to solve this problem, a low-level temporal segmentation algorithm based on cosine distance is proposed, hierarchical clustering is explored so that similar velocity vectors are clustered together according to the cosine distance in a progressive way, the center of each cluster is updated as the vector derived with linear regression, the segment boundaries are determined as the point when the cosine distance between adjacent velocity vectors is greater than 1 (angle>90 degrees). We have conducted experiments on the motion capture database provided by Carnegie Mellon University (CMU), the experiment results show that the performance of the proposed method is optimistic.

목차

Abstract
 1. Introduction
 2. Preprocessing of Data
  2.1 Feature Extraction
  2.2 Noise Elimination
  2.3 Dimension Reduction
 3. Segmentation Method
 4. Results and Discussion
 5. Conclusions
 Acknowledgements
 References

키워드

저자

• Yang Yang [ School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, China ]
• Jinfu Chen [ School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, China ]
• Zhanzhan Liu [ North Information Control Group Co., Ltd., Nanjing 210000, China ]
• Yongzhao Zhan [ School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, China ]
• Xinyu Wang [ School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605