boofcv.examples.stereo

Class ExampleFundamentalMatrix

java.lang.Object

boofcv.examples.stereo.ExampleFundamentalMatrix

public class ExampleFundamentalMatrix
extends java.lang.Object

A Fundamental matrix describes the epipolar relationship between two images. If two points, one from each image, match, then the inner product around the Fundamental matrix will be zero. If a fundamental matrix is known, then information about the scene and its structure can be extracted. Below are two examples of how a Fundamental matrix can be computed using different. The robust technique attempts to find the best fit Fundamental matrix to the data while removing noisy matches, The simple version just assumes that all the matches are correct. Similar techniques can be used to fit various other types of motion or structural models to observations. The input image and associated features are displayed in a window. In another window, inlier features from robust model fitting are shown.

Constructor Summary

Constructors

Constructor and Description
ExampleFundamentalMatrix()

Method Summary

Modifier and Type	Method and Description
static java.util.List<AssociatedPair>	computeMatches(java.awt.image.BufferedImage left, java.awt.image.BufferedImage right) Use the associate point feature example to create a list of AssociatedPair for use in computing the fundamental matrix.
static void	main(java.lang.String[] args)
static org.ejml.data.DenseMatrix64F	robustFundamental(java.util.List<AssociatedPair> matches, java.util.List<AssociatedPair> inliers) Given a set of noisy observations, compute the Fundamental matrix while removing the noise.
static org.ejml.data.DenseMatrix64F	simpleFundamental(java.util.List<AssociatedPair> matches) If the set of associated features are known to be correct, then the fundamental matrix can be computed directly with a lot less code.

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

ExampleFundamentalMatrix

public ExampleFundamentalMatrix()

Method Detail

robustFundamental

public static org.ejml.data.DenseMatrix64F robustFundamental(java.util.List<AssociatedPair> matches,
                                                             java.util.List<AssociatedPair> inliers)

Given a set of noisy observations, compute the Fundamental matrix while removing the noise.

Parameters:

matches - List of associated features between the two images

inliers - List of feature pairs that were determined to not be noise.

Returns:

The found fundamental matrix.

simpleFundamental

public static org.ejml.data.DenseMatrix64F simpleFundamental(java.util.List<AssociatedPair> matches)

If the set of associated features are known to be correct, then the fundamental matrix can be computed directly with a lot less code. The down side is that this technique is very sensitive to noise.

computeMatches

public static java.util.List<AssociatedPair> computeMatches(java.awt.image.BufferedImage left,
                                                            java.awt.image.BufferedImage right)

Use the associate point feature example to create a list of AssociatedPair for use in computing the fundamental matrix.

main

public static void main(java.lang.String[] args)