NDLI: Wide baseline stereo matching based on scale invariant feature transformation with hybrid geometric constraints

Content Provider	IET Digital Library
Author	Yang, Huachao Yu, Mei Zhang, Shubi
Abstract	Wide baseline stereo matching is a challenging task because of the presence of significant geometric deformations and illumination changes within the images. Based on the scale invariant feature transformation (SIFT) algorithm, this study proposes a new hybrid matching scheme that uses both the feature-based and the area-based methods to find reliable matches from sparse to dense under different geometric constraints. Firstly, the authors propose a SIFT-based robust weighted least squares matching (LSM) method modelled by a two-dimensional (2D) projective transformation to establish the initial correspondences and their local homographies. In this method, a normalised cross correlation metric modified with an adaptive scale and an orientation of the SIFT features (SIFT-NCC) is proposed to find a good initial alignment for the SIFT-LSM. Secondly, a robust matching propagation using the SIFT-NCC starts from the initial matches under an epipolar geometry and the local homography constraints; geometrical consistency checking is used simultaneously to identify the false matches. Thirdly, they use an improved, feature-based SIFT matching method to find the correspondences from the points that are not coplanar in the 3D space under an epipolar constraint only. A bidirectional selection strategy is used to remove the error matches.
Starting Page	611
Ending Page	619
Page Count	9
ISSN	17519632
Volume Number	8
e-ISSN	17519640
Issue Number	Issue 6, Dec (2014)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/8/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2013.0265
Journal	IET Computer Vision
Publisher Date	2014-03-26
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	2D Projective Transformation 3D Space Adaptive Scale Area-based Method Bidirectional Selection Strategy Combinatorial Mathematics Computer Vision And Image Processing Technique Epipolar Constraint Epipolar Geometry Error Matches Feature-based Method Feature-based SIFT Matching Method Geometric Deformations Geometrical Consistency Checking Geometry Hybrid Geometric Constraint Hybrid Matching Scheme Illumination Changes Image Matching Image Recognition Local Homography Constraint LSM Method Normalised Cross Correlation Metric Robust Matching Propagation Scale Invariant Feature Transformation Algorithm SIFT Algorithm SIFT Feature SIFT-based Robust Weighted Least Squares Matching SIFT-LSM SIFT-NCC Stereo Image Processing Wide Baseline Stereo Matching
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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