Pose synthesis using the inverse of jacobian matrix learned from examples

  • Chunpeng L
  • Shihong X
  • Zhaoqi W
  • 18


    Mendeley users who have this article in their library.
  • 5


    Citations of this article.


This paper presents a method of pose synthesis based on a low-dimensional space and a set of characteristics of motion learned from examples. This method consists of two phases: learning and synthesis. In the learning phase, a low-dimensional and discrete representation of the space of natural poses is constructed by using a self organizing map (SOM). Meanwhile, a set of matrices is extracted from the motion data. These matrices describe how the poses change with the end-effectors' positions, and play a key role in synthesizing natural looking results. In the synthesis phase, a lightweight algorithm based on the learned parameters is used. The synthesis process is very efficient because there is no time-consuming calculation, like numeric optimization or matrix inverting. Compared with other methods, our method not only can produce natural looking poses in real-time, but also works well with constraints positioned in a larger range. We apply our method in applications of interactive pose editing, real-time motion modification, and pose reconstruction from image. The results have proven the robustness and effectiveness of our method

Author-supplied keywords

  • Character animation
  • Inverse kinematics
  • Jacobian matrix
  • Self organizing map

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document


Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free