Motion analysis of articulated objects from monocular images

Xiaoyun Zhang, Yuncai Liu, Thomas S. Huang

Research output: Contribution to journalArticlepeer-review


This paper presents a new method of motion analysis of articulated objects from feature point correspondences over monocular perspective images without imposing any constraints on motion. An articulated object is modeled as a kinematic chain consisting of joints and links, and its 3D joint positions are estimated within a scale factor using the connection relationship of two links over two or three images. Then, twists and exponential maps are employed to represent the motion of each link, including the general motion of the base link and the rotation of other links around their joints. Finally, constraints from image point correspondences, which are similar to that of the essential matrix in rigid motion, are developed to estimate the motion. In the algorithm, the characteristic of articulated motion, i.e., motion correlation among links, is applied to decrease the complexity of the problem and improve the robustness. A point pattern matching algorithm for articulated objects is also discussed in this paper. Simulations and experiments on real images show the correctness and efficiency of the algorithms.

Original languageEnglish (US)
Pages (from-to)625-636
Number of pages12
JournalIEEE transactions on pattern analysis and machine intelligence
Issue number4
StatePublished - Apr 2006


  • Articulated object
  • Exponential map
  • Kinematic chain
  • Motion estimation
  • Point pattern matching

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics


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