Results 161 to 170 of about 369,007 (214)

An Inverse Generalized Conversion Filter for State Estimation in Nonlinear Adversarial Sensing Systems. [PDF]

Sensors (Basel)
Xi YA, Dong XH, Wu SY.
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Mineral Admixture Governs the Synergy of Polymer and Fibers in Ultra-Low Temperature Concrete. [PDF]

Materials (Basel)
Li Y, Deng Y.
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Optimal Selection of Biodegradable Polymer Composites for Load-Bearing Bone Tissue Engineering: A Hybrid Fuzzy AHP-TOPSIS Framework with Sensitivity-Based Robustness Analysis. [PDF]

J Funct Biomater
Hamidat L, Uzun Ozsahin D, Uzun B.
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A lightweight zero thermal expansion magnesium alloy. [PDF]

Nat Commun
Huang Y, Wu S, Dong Z, Song J, Wu G, Wang C, Bai S, Brault P, Jiang B, Pan F.   +9 more
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On the fundamental bordered matrix of linear estimation [PDF]

, 1990
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On the Direct Estimation of the Fundamental Matrix

2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007
The fundamental matrix is a central construct in the analysis of images captured from a pair of cameras and many feature-based methods have been proposed for its computation. In this paper, we propose a direct method for estimating the fundamental matrix where the motion between the frames is small (e.g. between successive frames of a video).
Yaser Sheikh, Asaad Hakeem, Mubarak Shah
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Robust estimation of the fundamental matrix

2010 IEEE International Conference on Image Processing, 2010
Most approaches to estimate the fundamental matrix assume a Gaussian distribution in the errors in view of mathematical tractability. However, this assumption is violated if the distribution computed is not normal. In this paper we propose a robust approach of estimating the fundamental matrix which does not rely on the Gaussian assumption.
Huiyu Zhou 0001, Gerald Schaefer
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On Accurate and Robust Estimation of Fundamental Matrix

Procedings of the British Machine Vision Conference 1996, 1996
This paper is concerned with accurate and robust estimation of the fundamental matrix. We show that, given certain conditions, a basic linear algorithm can yield excellent accuracy, in some cases two orders of magnitude better than sophisticated algorithms.
Bober, M, Georgis, N, Kittler, J
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Tensor Embedding of the Fundamental Matrix

1998
We revisit the bilinear matching constraint between two perspective views of a 3D scene. Our objective is to represent the constraint in the same manner and form as the trilinear constraint among three views. The motivation is to establish a common terminology that bridges between the fundamental matrix F (associated with the bilinear constraint) and ...
Shai Avidan, Amnon Shashua
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A stability analysis of the Fundamental matrix

1994
The Fundamental matrix is a key concept when working with uncalibrated images and multiple viewpoints. It contains all the available geometric information and enables to recover the epipolar geometry from uncalibrated perspective views. This paper is about a stability analysis for the Fundamental matrix.
Quang-Tuan Luong, Olivier D. Faugeras
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