Fast hierarchical clustering and other applications of dynamic closest pairs
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Video Google: A Text Retrieval Approach to Object Matching in Videos
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Photo tourism: exploring photo collections in 3D
ACM SIGGRAPH 2006 Papers
Modeling the World from Internet Photo Collections
International Journal of Computer Vision
Vision-based global localization and mapping for mobile robots
IEEE Transactions on Robotics
Coarse-to-fine vision-based localization by indexing scale-Invariant features
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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This paper proposes an algorithm to detect unnecessary image pairs for efficient structure from motion. Since image pair with small baseline is considered as a poor condition for reconstruction, we focus on computing cameras closely located. We address a term, "remoteness" which indicates the distance between two images in this paper. The remoteness is not affected by image's intrinsic parameters because camera intrinsic matrix is applied to put the extracted features in the normalized coordinate. The remoteness is computed using feature disparity in normalized coordinate. Therefore, we can detect redundant image pair captured at the near position without reconstruction. The proposed algorithm is proved by experimental results with Notre Dame images.