Binocular Image Flows: Steps Toward Stereo-Motion Fusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Three-dimensional motion computation and object segmentation in a long sequence of stereo frames
International Journal of Computer Vision
Shape and motion from image streams under orthography: a factorization method
International Journal of Computer Vision
A paraperspective factorization method for shape and motion recovery
ECCV '94 Proceedings of the third European conference on Computer Vision (Vol. II)
Constraint, optimization, and hierarchy: reviewing stereoscopic correspondence of complex features
Computer Vision and Image Understanding
A Sequential Factorization Method for Recovering Shape and Motion From Image Streams
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Multibody Factorization Method for Independently Moving Objects
International Journal of Computer Vision
Theory of Reconstruction from Image Motion
Theory of Reconstruction from Image Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Motion - Stereo Integration for Depth Estimation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Stereo and motion correspondences using nonlinear optimization method
Computer Vision and Image Understanding
Image and Vision Computing
Epiflow-A paradigm for tracking stereo correspondences
Computer Vision and Image Understanding
Stereo and motion correspondences using nonlinear optimization method
Computer Vision and Image Understanding
Image correspondence from motion subspace constraint and epipolar constraint
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
New measurements for stereo-motion correspondences
ICCOMP'06 Proceedings of the 10th WSEAS international conference on Computers
3D information extraction using Region-based Deformable Net for monocular robot navigation
Journal of Visual Communication and Image Representation
Quasi-Parallax for Nearly Parallel Frontal Eyes
International Journal of Computer Vision
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This paper presents a new approach of combining stereo vision and dynamic vision with the objective of retaining their advantages and removing their disadvantages. It is shown that, by assuming affine cameras, the stereo correspondences and motion correspondences, if organized in a particular way in a matrix, can be decomposed into the 3D structure of the scene, the camera parameters, the motion parameters, and the stereo geometry. With this, the approach can infer stereo correspondences from motion correspondences, requiring only a time linear with respect to the size of the available image data. The approach offers the advantages of simpler correspondence, as in dynamic vision, and accurate reconstruction, as in stereo vision, even with short image sequences.