Motion estimation without correspondences and object tracking over long time sequences

Dmitry B. Goldgof, Hua Lee, Thomas S. Huang

Research output: Contribution to journalConference articlepeer-review


This paper presents moment-based algorithms for matching and motion estimation of 3-D point or line sets and application of these algorithms to object tracking over long time sequences. The motion analysis is done by identifying two sets of coordinate directions based on relative position of points (or lines) before and after the motion. Since these coordinate vectors are motion invariant, the relationship between them gives parameters of rigid motion. However, we need to verify that the sets before and after the motion are matched before applying motion estimation algorithm. We propose several measures suitable for matching of 3-D point (and line) sets, test them on simulated data and develop several criteria for determining noise sensitivity of matching and motion estimation algorithms. Finally, we apply the proposed algorithm to the long sequence (24) of real data (moving vehicle) on which 3-D points were determined by stero matching.

Original languageEnglish (US)
Pages (from-to)109-121
Number of pages13
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - 1991
Externally publishedYes
EventSensor Fusion III: 3-D Perception and Recognition - Boston, MA, USA
Duration: Nov 5 1990Nov 8 1990

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


Dive into the research topics of 'Motion estimation without correspondences and object tracking over long time sequences'. Together they form a unique fingerprint.

Cite this