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Stereo by intra- and inter-scanline search using dynamic programming.

Y Ohta1, T Kanade

  • 1Institute of Information Sciences and Electronics, University of Tsukuba, Ibaraki, 305, Japan.

IEEE Transactions on Pattern Analysis and Machine Intelligence
|August 27, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a novel stereo matching algorithm using dynamic programming for accurate image correspondence. The method efficiently searches for matching paths across scanlines, improving stereo vision accuracy.

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Area of Science:

  • Computer Vision
  • Image Processing
  • Computational Geometry

Background:

  • Stereo matching is crucial for 3D reconstruction.
  • Existing methods face challenges with accuracy and computational cost.
  • The need for robust algorithms that handle image inconsistencies is high.

Purpose of the Study:

  • To develop an efficient stereo matching algorithm using dynamic programming.
  • To improve the accuracy of correspondence finding in stereo images.
  • To leverage edge information for enhanced matching consistency.

Main Methods:

  • A dynamic programming approach is employed for stereo matching.
  • The algorithm utilizes both inter-scanline and intra-scanline searches.
  • Edge-delimited intervals are used as matching elements with an interval-based similarity metric.

Main Results:

  • The algorithm successfully finds correspondences between rectified stereo images.
  • It effectively utilizes vertical edge consistency constraints across scanlines.
  • The dynamic programming approach optimizes both search dimensions simultaneously.

Conclusions:

  • The proposed algorithm offers an effective solution for stereo matching.
  • It demonstrates robust performance across various image types.
  • The integration of dynamic programming enhances computational efficiency and accuracy.