Stereo Image Dense Matching Based on SGM Constrained by Feature Matching

Dense image matching plays a important role in stereo vision and remote sensing. Semi-global matching (SGM) is a widely used dense image matching framwork, which uses dynamic programming calculation strategy to optimize the global energy function. SGM has the problem of wrong disparity accumulation...

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Bibliographic Details
Published in2023 9th International Conference on Computer and Communications (ICCC) pp. 1911 - 1915
Main Authors Ma, Tao, Zhu, Hangbiao, Huang, Weijian, An, Pei, Wang, Chun, Yu, Kun
Format Conference Proceeding
LanguageEnglish
Published IEEE 08.12.2023
Subjects
Costs
Dense Image Matching
Dynamic programming
Feature extraction
Feature Matching
Filtering
Image matching
Reference Points
Reliability
Semi-Global Matching (SGM)
Stereo vision
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Summary:Dense image matching plays a important role in stereo vision and remote sensing. Semi-global matching (SGM) is a widely used dense image matching framwork, which uses dynamic programming calculation strategy to optimize the global energy function. SGM has the problem of wrong disparity accumulation along the path. To solve the problem, this paper proposes a new dense image matching method based on feature matching and SGM. First, the feature matching is used to extract the reliable reference points. And then, reference points are used as additional constraints in matching cost aggregation to cut off the wrong disparity delivering along the path. In order to evaluate our method, qualitative and quantitative experiments are carried out on three stereo image pairs. The experimental results show that our method can achieve high matching accuracy by effectively reducing the error propagation.
ISSN:2837-7109
DOI:10.1109/ICCC59590.2023.10507454