The MatlabBGL library fills a hole in Matlab s suite of algorithms. Namely, it provides a rich set of algorithms to work with graphs, as in graph theory graphs. The MatlabBGL package uses Matlab s native sparse Matrix type as a graph and provides algorithms that work
圖的深度優先遍歷和廣度優先遍歷，以鄰接矩陣方式輸入。（按照提示輸入）！ - The chart depth first spreads the calendar and the breadth first spreads the calendar, is next the Matrix way input. (According
This paper introduces an affine invariant of trapezia, and the explicit constraint equation between the intrinsic Matrix of a camera and the similarity invariants of a trapezium are established using the affine invariant. By this constraint, the inner parameters, motion parameters of the cameras and the similarity invariants of trapezia can be linearly determined using some prior knowledge on the cameras or the trapezia. The proposed algorithms have wide applicability since parallel lines are not rare in many scenes. Experimental results validate the proposed approaches. This work presents a unifying framework based on the parallelism constraint, and the previous methods based on the parallelograms or the parallelepipeds can be integrated into this framework.
Key words: invariant parallelism constraint camera calibration 3D reconstruction
ICP fit points in data to the points in model. Fit with respect to minimize the sum of square errors with the closest model points and data points.
Ordinary usage:
[R, T] = icp(model,data)
INPUT:
model - Matrix with model points,
data - Matrix with data points,
OUTPUT:
R - rotation Matrix and
T - translation vector accordingly
so
newdata = R*data + T .
newdata are transformed data points to fit model
see help icp for more information
#if !defined(AFX_GAQUEEN_H__C26AE0A3_F9B4_426F_A324_B460CC7946CB__INCLUDED_)
#define AFX_GAQUEEN_H__C26AE0A3_F9B4_426F_A324_B460CC7946CB__INCLUDED_
#if _MSC_VER > 1000
#pragma once
#endif // _MSC_VER > 1000
class CGAQueen
{
public:
CGAQueen(int nPopulation,int nIteration,float Mutation,int mChBoard)
virtual ~CGAQueen()
void Clear() // to clear chess board with 0 value
void InitialPopulation() // to create the first and initial randompopulation
void FillArea(int index) // to fill chess board with desired chromosome
int CostFunc(int index) // determine the cost of Matrix[index][index]
void PopulationSort() // to sort population from the best to the worst
void GenerateCrossOverMatrix() // a way to create children from parent is CcrossOver
void Mating() // to create children from parents
void Ap
