Titlebook: Computer Vision -- ECCV 2006; 9th European Confere Aleš Leonardis,Horst Bischof,Axel Pinz Conference proceedings 2006 Springer-Verlag Berli

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Nonrigid Shape and Motion from Multiple Perspective Viewstraints among multiple views of a rigid shape are multilinear on the image points and can be reduced to bilinear (epipolar) and trilinear constraints among two and three views, respectively. In this paper, we generalize this classic result by showing that the constraints among multiple views of a no

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3D Surface Reconstruction Using Graph Cuts with Surface Constraintsused for optimization on a color consistency field. Constraints are added to improve its performance. These constraints are a set of predetermined locations that the true surface of the object is likely to pass through. They are used to preserve protrusions and to pursue concavities respectively in

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Trace Quotient Problems Revisitedf .which can be solved with the generalized eigenvalue decomposition approach. In this paper, we present a direct solution to the former formulation. First, considering that the feasible solutions are constrained on a Grassmann manifold, we present a necessary condition for the optimal solution of t

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Learning Nonlinear Manifolds from Time Seriesn recent years, conventional nonlinear dimensionality reduction algorithms have been designed to deal with stationary, or independent and identically distributed data. In this paper, we present a novel method that learns nonlinear mapping from time series data to their intrinsic coordinates on the u

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https://doi.org/10.1007/978-3-031-07082-2ment, usable for any object, while the second one is a closed-form linear solution valid for planar objects. The resulting algorithms enable us to transform a CMOS low cost and low power camera into an innovative and powerful velocity sensor. Finally, experimental results with real data confirm the relevance and accuracy of the approach.

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Augustin Bariant,Gaëtan Leurenta nonrigid quintifocal tensor, from which one can linearly compute nonrigid shape and motion. We also demonstrate the existence of intrinsic ambiguities in the reconstruction of camera translation, shape coefficients and shape bases. Examples show the effectiveness of our method on nonrigid scenes with significant perspective effects.

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https://doi.org/10.1007/978-3-031-30545-0ning and inference problems. Numerous experiments demonstrate the proposed method is able to learn nonlinear manifolds from time series data, and as a result of exploiting the temporal correlation, achieve superior results.