Abstract One well-known approach for reconstruction of a 3D object from two images obtained by calibrated cameras is based on the essential matrix computation. The extrinsic camera parameters can be found by decomposing the essential matrix into skew-symmetric and rotation parts, and then the reconstruction problem can be solved by triangulation. In this paper we present a direct way for such a...

We solve the Robust Principal Component Analysis problem: decomposing an observed matrix into a low-rank matrix plus a sparse matrix. Unlike alternative methods that approximate this l0 objective with an l1 objective and solve a convex optimization problem, we develop a corresponding generative model and solve a statistical inference problem. The main advantages of this approach is its ability ...

The solution representing a brane-anti-brane system in matrix models breaks the usual matrix spacetime symmetry. We show that the spacetime symmetry on the branes is not broken, rather appears as a combination of the matrix spacetime transformation and a gauge transformation. As a result, the tachyon field, itself an off-diagonal entry in longitudinal matrices, transforms nontrivially under rot...

Massive on–shell operator matrix elements and self-energy diagrams with outer gluon lines are calculated analytically at O(αs), using Mellin–Barnes integrals and representations through generalized hypergeometric functions. This method allows for a direct evaluation without decomposing the integrals using the integration-by-parts method.

This paper discusses an efficient parallel implementation of the ensemble Kalman filter based on the modified Cholesky decomposition. The proposed implementation starts with decomposing the domain into sub-domains. In each sub-domain a sparse estimation of the inverse background error covariance matrix is computed via a modified Cholesky decomposition; the estimates are computed concurrently on

In this paper, we propose a novel method for efficiently calculating the eigenvectors of uniformly rotated images of a set of templates. As we show, the images can be optimally approximated by a linear series of eigenvectors which can be calculated without actually decomposing the sample covariance matrix.

E nergy consumption has increased significantly in Iran during the recent decades. In this study, an inter-industrial model has been improved to investigate the sources of the changes in the energy consumption of the country. The input-output tables of Iran for the years 1988 and 2001 have been employed as the database of the model. The innovation of this research allows the researchers to stud...

Lunar habitat design is a complex endeavor characterized by complicated task-composition, numerous internal iterations, and intense task-coupling. The process of assembled building in terrestrial construction the system composition lunar habitats have been constructed. However, there insufficient experience to fully understand missions likewise coordination between architects various discipline...

We consider the problem of decomposing an integer matrix into a positively weighted sum of binary matrices that have the consecutive-ones property. This problem is well-known and of practical relevance. It has an important application in cancer radiation therapy treatment planning: the sequencing of multileaf collimators to deliver a given radiation intensity matrix, representing (a component o...