Journal
IEEE TRANSACTIONS ON IMAGE PROCESSING
Volume 23, Issue 1, Pages 308-318Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIP.2013.2290597
Keywords
Neighboring image selection; depth-map computation; 3D modeling
Funding
- Natural Science Foundation of China [61105032, 61333015]
- Strategic Priority Research Program of the Chinese Academy of Sciences [XDA06030300]
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Depth-map merging based 3D modeling is an effective approach for reconstructing large-scale scenes from multiple images. In addition to generate high quality depth maps at each image, how to select suitable neighboring images for each image is also an important step in the reconstruction pipeline, unfortunately to which little attention has been paid in the literature untill now. This paper is intended to tackle this issue for large scale scene reconstruction where many unordered images are captured and used with substantial varying scale and view-angle changes. We formulate the neighboring image selection as a combinatorial optimization problem and use the quantum-inspired evolutionary algorithm to seek its optimal solution. Experimental results on the ground truth data set show that our approach can significantly improve the quality of the depth-maps as well as final 3D reconstruction results with high computational efficiency.
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