Motion curves for parametric shape and motion estimation

Pierre Louis Bazin, Jean Marc Vézien

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


This paper presents a novel approach to camera motion parametrization for the structure and motion problem. In a model-based framework, the hypothesis of (relatively) continuous and smooth sensor motion enables to reformulate the motion recovery problem as a global curve estimation problem on the camera path. Curves of incremental complexity are fitted using model selection to take into account incoming image data. No first estimate guess is needed. The use of modeling curves lead to a meaningful description of the camera trajectories, with a drastic reduction in the number of degrees of freedom. In order to characterize the behaviour and performances of the approach, experiments with various long video sequences, both synthetic and real, are undertaken. Several candidate curve models for motion estimation are presented and compared, and the results validate the work in terms of reconstruction accuracy, noise robustness and model compacity.

Original languageEnglish (US)
Pages (from-to)262-276
Number of pages15
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
StatePublished - 2002
Externally publishedYes


  • Camera modeling
  • Model selection
  • Model-based estimation
  • Motion curves
  • Structure from motion

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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