Computing the cost of occlusion

Gabriel Fielding, Moshe Kam

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Recently, Cox et al. (1996, CVGIP: Image Understanding 63, 542-567) presented a new dynamic programming-based stereo matching algorithm. The algorithm uses a parameter which represents the cost of occlusion. This cost is levied if the algorithm decides that two measurements, each from a different camera along corresponding epipolar lines, are not projections of the same point in space. The occlusion cost is dependent on the standard deviation of the (Gaussian) sensor noise, σ, and the probability of match detection, PD. Under certain conditions such as low signal-to-noise ratio, the algorithm of Cox et al. will declare occlusions where they do not exist. We offer an alternative definition for the cost of occlusion, based on a decision-theoretic formulation for the matching process. This alternative improves the performance of the matching algorithm.

Original languageEnglish (US)
Pages (from-to)324-329
Number of pages6
JournalComputer Vision and Image Understanding
Volume79
Issue number2
DOIs
StatePublished - Aug 2000
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition

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