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Efficient path-based stereo matching with subpixel accuracy.

Arturo Donate¹, Xiuwen Liu, Emmanuel G Collins

¹Department of Computer Science, Florida State University, Tallahassee, FL 32306, USA. donate@cs.fsu.edu

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society

|June 24, 2010

Summary

This summary is machine-generated.

This study introduces an efficient path-based stereo matching algorithm for precise subpixel correspondences. By integrating bilinear interpolation with integral images, it achieves superior accuracy over existing methods.

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Area of Science:

Computer Vision
Image Processing
Photogrammetry

Background:

Traditional stereo matching algorithms struggle with local ambiguities and subpixel accuracy.
Path-based methods offer global optimization but require efficient subpixel refinement.

Purpose of the Study:

To develop an efficient algorithm for accurate subpixel matching in stereo images.
To enhance path-based stereo matching by enabling efficient subpixel cross-correlation computation.

Main Methods:

Implemented a path-based matching algorithm utilizing dynamic programming.
Introduced bilinear interpolation via integral images for efficient subpixel cross-correlation calculation.
Integrated subpixel cross-correlation computation into the global matching criterion.

Main Results:

Demonstrated efficient computation of cross-correlations at all subpixel locations.
Achieved subpixel accuracy in path-based stereo matching.
Showcased significant improvements over existing path-based matching methods.

Conclusions:

The proposed method enables accurate subpixel matching for stereo vision.
Efficient subpixel computation is crucial for high-accuracy path-based stereo matching.
The algorithm offers a feasible and improved solution for stereo correspondence problems.