Matching 3-D Line Segments with Applications to Multiple-Object Motion Estimation

Homer H. Chen, Thomas S. Huang

Research output: Contribution to journalArticlepeer-review


Feature-based motion analysis requires the corresponding features between frames be identified. Presented here is a two-stage algorithm for matching line segments using 3-D data. In the first stage, a tree-search based on the orientation of the line segments is applied to establish potential matches. The sign ambiguity of line segments is fixed by a simple congruency constraint. In the second stage, a Hough clustering technique based on the position of line segments is applied to verify potential matches. Any paired line segments of a match that cannot be brought to overlap by the translation determined by the clustering are removed from the match. Unlike previous methods, this algorithm combats noise more effectively and ensures the global consistency of a match. While the orginal motivation for the algorithm is for multiple-object motion estimation from stereo image sequences, the algorithm can also be applied to other domains, such as object recognition and object model construction from multiple views.

Original languageEnglish (US)
Pages (from-to)1002-1008
Number of pages7
JournalIEEE transactions on pattern analysis and machine intelligence
Issue number10
StatePublished - Oct 1990
Externally publishedYes


  • Correspondence analysis
  • Hough clustering
  • matching
  • motion estimation
  • object recognition
  • tree search

ASJC Scopus subject areas

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


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