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International Journal of Computer Vision
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International Journal of Computer Vision
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International Journal of Computer Vision
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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International Journal of Computer Vision
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Computer Vision and Image Understanding
International Journal of Computer Vision - 1998 Marr Prize
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ECCV '92 Proceedings of the Second European Conference on Computer Vision
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ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
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ACCV '98 Proceedings of the Third Asian Conference on Computer Vision-Volume II
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Factorization Methods for Projective Structure and Motion
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
The Modulus Constraint: A New Constraint for Self-Calibration
ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270
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International Journal of Computer Vision
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IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Circuits and Systems for Video Technology
Adaptive reconstruction of intermediate views from stereoscopic images
IEEE Transactions on Circuits and Systems for Video Technology
The quasi-perspective model: Geometric properties and 3D reconstruction
Pattern Recognition
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The paper addresses the problem of 3-D Euclidean structure and motion recovery from video sequences based on perspective factorization. It is well known that projective depth recovery and camera calibration are two essential and difficult steps in metric reconstruction. We focus on the difficulties and propose two new algorithms to improve the performance of perspective factorization. First, we propose to initialize the projective depths via a projective structure reconstructed from two views with large camera movement, and optimize the depths iteratively by minimizing reprojection residues. The algorithm is more accurate than previous methods and converges quickly. Second, we propose a self-calibration method based on the Kruppa constraint to deal with more general camera model. The Euclidean structure can be recovered from factorization of the normalized tracking matrix. Extensive experiments on synthetic data and real sequences are performed to validate the proposed method and good improvements are observed.