Projective Reconstruction and Invariants from Multiple Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rigidity Checking of 3D Point Correspondences Under Perspective Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
In Defense of the Eight-Point Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Determining the Epipolar Geometry and its Uncertainty: A Review
International Journal of Computer Vision
An optimal algorithm for approximate nearest neighbor searching fixed dimensions
Journal of the ACM (JACM)
ROR: Rejection of Outliers by Rotations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computational Framework for Segmentation and Grouping
Computational Framework for Segmentation and Grouping
Layered 4D Representation and Voting for Grouping from Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
High-accuracy stereo depth maps using structured light
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
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The problem of recovering the 3-D camera and scene structure has been intensively studied and is considered well understood. Starting with two images, a process of establishing point correspondences is usually followed by the estimation of epipolar geometry while also rejecting outlier matches, and finally by 3-D structure estimation. However, most existing methods tend to fail in the combined presence of noise and multiple motions, since no single constraint applies to the entire set of matches. Hence, image registration becomes a more challenging problem, as the matching and registration phases become interdependent. We propose a novel approach that decouples the above operations, allowing for separate handling of matching, outlier rejection, grouping and 3-D interpretation. Our method first determines an accurate representation in terms of dense velocities, segmented motion regions and boundaries, by enforcing only the smoothness of image motion, followed by the extraction of 3-D camera and scene geometry.