JOURNAL ARTICLE

Half-resolution semi-global stereo matching

Abstract

Semi-global matching is a popular choice for applications where dense and robust stereo estimation is required and real-time performance is crucial. It therefore plays an important role in vision-based driver assistance systems. The strength of the algorithm comes from the integration of multiple 1D energy paths which are minimized along eight different directions across the image domain. The contribution of this paper is twofold. First, a thorough evaluation of stereo matching quality is performed when the number of accumulation paths is reduced. Second, an alteration of semi-global matching is proposed that operates only on half of the image domain without losing disparity resolution. The evaluation is performed on four real-world driving sequences of 400 frames each, as well as on 396 frames of a synthetic image sequence where sub-pixel accurate ground truth is available. Results indicate that a reduction of accumulation paths is a very good option to improve the run-time performance without losing significant quality, even on sub-pixel level. Furthermore, operating semiglobal matching only on half the image yields almost identical results to the corresponding full path integration. This approach yields the potential to further speed up the runtime and could also be exploited for other alterations of the algorithm.

Keywords:
Matching (statistics) Computer science Pixel Artificial intelligence Computer vision Image (mathematics) Path (computing) Ground truth Image resolution Domain (mathematical analysis) Sequence (biology) Image quality Algorithm Mathematics

Metrics

26
Cited By
3.33
FWCI (Field Weighted Citation Impact)
22
Refs
0.94
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Video Coding and Compression Technologies
Physical Sciences →  Computer Science →  Signal Processing

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