Results 261 to 270 of about 4,693,472 (296)

A robust algorithm to estimate the fundamental matrix

Pattern Recognition Letters, 2000
Abstract A new method, the biepipole constraint algorithm, is developed to estimate the fundamental matrix (F-matrix) based on an 8-parameter model and the geometrical analysis. First, through the analysis of the new constraints, the four parameters of the F-matrix can be estimated by solving a nonlinear unconstraint optimization problem.
Chen, Z., Wu, C., Shen, P., Liu, Y., Quan, Long   +4 more
openaire   +2 more sources

On a fundamental property of the cross- Gramian matrix

IEEE Transactions on Circuits and Systems, 1984
Summary: The cross-Gramian matrix \(W_{c0}(T)\) for linear single-input single- output (SISO) dynamical systems has been related to the controllability and observability Gramians via \(W^ 2_{c0}(T)=W_ c(T)W_ 0(T)\) for \(T=\infty\). The result is now proved for any arbitrary time interval T, and is extended to symmetric multivariable systems which have
Fernando, K. V., Nicholson, H.
openaire   +1 more source

Highest Accuracy Fundamental Matrix Computation

2007
We compare algorithms for fundamental matrix computation, which we classify into "a posteriori correction", "internal access", and "external access". Doing experimental comparison, we show that the 7-parameter Levenberg-Marquardt (LM) search and the extended FNS (EFNS) exhibit the best performance and that additional bundle adjustment does not increase
Yasuyuki Sugaya, Ken-ichi Kanatani
openaire   +2 more sources

Discretization effects in the fundamental matrix computation

2012 19th IEEE International Conference on Image Processing, 2012
A polyhedron represents the solution set of an approximate system modeling the epipolar constraints. We introduce a new robust approach for the computation of the fundamental matrix taking into account the intrinsic errors involved in the discretization process.
openaire   +2 more sources

Randomized Acceleration of Fundamental Matrix Computations

2002
We accentuate the power of several known effective methods by combining them together and adding some novel techniques. As a result, we substantially improve the known record randomized bit-operation complexity estimates for various fundamental computations with integer matrices.
openaire   +2 more sources

Fundamental Matrix

2008
Shashi Shekhar, Hui Xiong
openaire   +1 more source

Kruppa's Equations Derived From the Fundamental Matrix

IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997
R I Hartley
exaly  

Threading Fundamental Matrices

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2001
A Shashua
exaly  

Matrix Fundamentals

Edward Barry Saff, Arthur David Snider
openaire   +1 more source

Estimating the Fundamental Matrix via Constrained Least-Squares: A Convex Approach

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002
Andrea Garulli, Antonio Vicino, Roberto Cipolla   +2 more
exaly