Probabilistic model for recovering camera translation

Ranxiao Frances Wang, James E. Cutting

Research output: Contribution to journalArticlepeer-review


This paper describes the mathematical basis and application of a probabilistic model for recovering the direction of camera translation (heading) from optical flow. According to the theorem that heading cannot lie between two converging points in a stationary environment, one can compute the posterior probability distribution of heading across the image and choose the heading with maximum a posteriori (MAP). The model requires very simple computation, provides confidence level of the judgments, applies to both linear and curved trajectories, functions in the presence of camera rotations, and exhibited high accuracy up to 0.1°-0.2° in random dot simulations.

Original languageEnglish (US)
Pages (from-to)205-212
Number of pages8
JournalComputer Vision and Image Understanding
Issue number3
StatePublished - Dec 1999

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition


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