Multi-view correspondence by enforcement of rigidity constraints
Image and Vision Computing
Optimal multi-frame correspondence with assignment tensors
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Finding correspondence from multiple images via sparse and low-rank decomposition
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
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We propose a solution to the n-frame correspondence problem under the factorization framework. During the matching process, our algorithm takes explicitly into account the geometrical constraints associated to the reconstruction process. To this end, a rank constraint is imposed on the measurement matrix. Since our method relies solely on geometric constraints, it is not dependent on corners as image features and can consequently match generic points (e.g. contours). Outlier rejection is integrated as a part of the actual matching process. In general the problem is formulated as combinatorial, but we develop a method which can provide a solution with a low computational complexity. Because of this, our algorithm is able to handle high-dimensional matching problems that are common in real-life applications.