Articulated joint estimation from motion using two monocular images

Xiaoyun Zhang, Yuncai Liu, Thomas S. Huang

Research output: Contribution to journalArticle

Abstract

Motion can provide useful information about the structure of an articulated object. In this paper, we develop a method to estimate the revolute joints from two monocular images of the moving articulated object. Firstly, according to the characteristic of the articulated structure and motion, constraint equations about motion and joint parameters from image point correspondences are deduced, which provide crucial information for joint estimation. Then, the position ambiguity caused by the one DOF attribute, and the scale ambiguity resulted from monocular images are discussed. Also, a skillful function is employed to avoid the degeneration cases of estimation. Finally, the joint axis are computed from the estimated rotation matrices, and all estimated joint points are scaled to have the same scale factor to their ground truth. Simulations and experiments on real images show the correctness and efficiency of the algorithm.

Original languageEnglish (US)
Pages (from-to)1097-1106
Number of pages10
JournalPattern Recognition Letters
Volume25
Issue number10
DOIs
StatePublished - Jul 16 2004
Externally publishedYes

Keywords

  • Articulated object
  • Kinematic chain
  • Motion estimation
  • Revolute joint

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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