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Local-Adaptive Image Alignment Based on Triangular Facet Approximation
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DOI：10.1109/TIP.2019.2949424.png)
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Abstract
En 中文
Accurate and efficient image alignment is the core problem in the research of panoramic stitching nowadays. This paper proposes a local-adaptive image alignment method based on triangular facet approximation, which directly manipulates the matching data in the camera coordinates, and therefore rises superior to the imaging model of cameras. A more robust planar transformation model is proposed and extended to be local-adaptive via combining it with two weighting strategies. By approximating the scene as a combination of adjacent triangular facets, the planar and spherical triangulation strategies are introduced to more efficiently align normal and fisheye images respectively. The efficiency of the proposed method are verified through the comparative experiments on several challenging cases both qualitatively and quantitatively.
Keywords:
Cameras
Data models
Distortion
Strain
Technological innovation
Computational efficiency
Computer vision
image stitching
image alignment
parallax handling
triangular meshing
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