我正在编写一些代码来使用一系列位置来动画一个点。为了获得不错的结果，我想添加一些样条插值 平滑位置之间的过渡。所有职位都以相同的时间间隔（比方说500毫秒）。
int delay = 500;
vector<Point> positions={ (0, 0) , (50, 20), (150, 100), (30, 120) };
以下是我所做的线性插值（似乎工作正常），juste让你知道我以后要找的东西：
Point getPositionAt(int currentTime){
Point before, after, result;
int currentIndex = (currentTime / delay) % positions.size();
before = positions[currentIndex];
after = positions[(currentIndex + 1) % positions.size()];
// progress between [before] and [after]
double progress = fmod((((double)currentTime) / (double)delay), (double)positions.size()) - currentIndex;
result.x = before.x + (int)progress*(after.x - before.x);
result.y = before.y + (int)progress*(after.y - before.y);
return result;
}
所以这很简单，但现在我想做的是样条插值。谢谢！
答案 0 :(得分：1)
我必须为＆＃34;实体＆＃34;写一个Bezier样条曲线创建例程。这是我正在努力的游戏中的一条路径。我创建了一个基类来处理＆＃34; SplineInterface＆＃34;和创建的两个派生类，一个基于经典样条技术（例如Sedgewick / Algorithms），另一个基于Bezier Splines。
这是代码。它是一个单独的头文件，包含一些包含（大多数应该是显而易见的）：
#ifndef __SplineCommon__
#define __SplineCommon__
#include "CommonSTL.h"
#include "CommonProject.h"
#include "MathUtilities.h"
/* A Spline base class. */
class SplineBase
{
private:
vector<Vec2> _points;
bool _elimColinearPoints;
protected:
protected:
/* OVERRIDE THESE FUNCTIONS */
virtual void ResetDerived() = 0;
enum
{
NOM_SIZE = 32,
};
public:
SplineBase()
{
_points.reserve(NOM_SIZE);
_elimColinearPoints = true;
}
const vector<Vec2>& GetPoints() { return _points; }
bool GetElimColinearPoints() { return _elimColinearPoints; }
void SetElimColinearPoints(bool elim) { _elimColinearPoints = elim; }
/* OVERRIDE THESE FUNCTIONS */
virtual Vec2 Eval(int seg, double t) = 0;
virtual bool ComputeSpline() = 0;
virtual void DumpDerived() {}
/* Clear out all the data.
*/
void Reset()
{
_points.clear();
ResetDerived();
}
void AddPoint(const Vec2& pt)
{
// If this new point is colinear with the two previous points,
// pop off the last point and add this one instead.
if(_elimColinearPoints && _points.size() > 2)
{
int N = _points.size()-1;
Vec2 p0 = _points[N-1] - _points[N-2];
Vec2 p1 = _points[N] - _points[N-1];
Vec2 p2 = pt - _points[N];
// We test for colinearity by comparing the slopes
// of the two lines. If the slopes are the same,
// we assume colinearity.
float32 delta = (p2.y-p1.y)*(p1.x-p0.x)-(p1.y-p0.y)*(p2.x-p1.x);
if(MathUtilities::IsNearZero(delta))
{
_points.pop_back();
}
}
_points.push_back(pt);
}
void Dump(int segments = 5)
{
assert(segments > 1);
cout << "Original Points (" << _points.size() << ")" << endl;
cout << "-----------------------------" << endl;
for(int idx = 0; idx < _points.size(); ++idx)
{
cout << "[" << idx << "]" << " " << _points[idx] << endl;
}
cout << "-----------------------------" << endl;
DumpDerived();
cout << "-----------------------------" << endl;
cout << "Evaluating Spline at " << segments << " points." << endl;
for(int idx = 0; idx < _points.size()-1; idx++)
{
cout << "---------- " << "From " << _points[idx] << " to " << _points[idx+1] << "." << endl;
for(int tIdx = 0; tIdx < segments+1; ++tIdx)
{
double t = tIdx*1.0/segments;
cout << "[" << tIdx << "]" << " ";
cout << "[" << t*100 << "%]" << " ";
cout << " --> " << Eval(idx,t);
cout << endl;
}
}
}
};
class ClassicSpline : public SplineBase
{
private:
/* The system of linear equations found by solving
* for the 3 order spline polynomial is given by:
* A*x = b. The "x" is represented by _xCol and the
* "b" is represented by _bCol in the code.
*
* The "A" is formulated with diagonal elements (_diagElems) and
* symmetric off-diagonal elements (_offDiagElemns). The
* general structure (for six points) looks like:
*
*
* | d1 u1 0 0 0 | | p1 | | w1 |
* | u1 d2 u2 0 0 | | p2 | | w2 |
* | 0 u2 d3 u3 0 | * | p3 | = | w3 |
* | 0 0 u3 d4 u4 | | p4 | | w4 |
* | 0 0 0 u4 d5 | | p5 | | w5 |
*
*
* The general derivation for this can be found
* in Robert Sedgewick's "Algorithms in C++".
*
*/
vector<double> _xCol;
vector<double> _bCol;
vector<double> _diagElems;
vector<double> _offDiagElems;
public:
ClassicSpline()
{
_xCol.reserve(NOM_SIZE);
_bCol.reserve(NOM_SIZE);
_diagElems.reserve(NOM_SIZE);
_offDiagElems.reserve(NOM_SIZE);
}
/* Evaluate the spline for the ith segment
* for parameter. The value of parameter t must
* be between 0 and 1.
*/
inline virtual Vec2 Eval(int seg, double t)
{
const vector<Vec2>& points = GetPoints();
assert(t >= 0);
assert(t <= 1.0);
assert(seg >= 0);
assert(seg < (points.size()-1));
const double ONE_OVER_SIX = 1.0/6.0;
double oneMinust = 1.0 - t;
double t3Minust = t*t*t-t;
double oneMinust3minust = oneMinust*oneMinust*oneMinust-oneMinust;
double deltaX = points[seg+1].x - points[seg].x;
double yValue = t * points[seg + 1].y +
oneMinust*points[seg].y +
ONE_OVER_SIX*deltaX*deltaX*(t3Minust*_xCol[seg+1] - oneMinust3minust*_xCol[seg]);
double xValue = t*(points[seg+1].x-points[seg].x) + points[seg].x;
return Vec2(xValue,yValue);
}
/* Clear out all the data.
*/
virtual void ResetDerived()
{
_diagElems.clear();
_bCol.clear();
_xCol.clear();
_offDiagElems.clear();
}
virtual bool ComputeSpline()
{
const vector<Vec2>& p = GetPoints();
_bCol.resize(p.size());
_xCol.resize(p.size());
_diagElems.resize(p.size());
for(int idx = 1; idx < p.size(); ++idx)
{
_diagElems[idx] = 2*(p[idx+1].x-p[idx-1].x);
}
for(int idx = 0; idx < p.size(); ++idx)
{
_offDiagElems[idx] = p[idx+1].x - p[idx].x;
}
for(int idx = 1; idx < p.size(); ++idx)
{
_bCol[idx] = 6.0*((p[idx+1].y-p[idx].y)/_offDiagElems[idx] -
(p[idx].y-p[idx-1].y)/_offDiagElems[idx-1]);
}
_xCol[0] = 0.0;
_xCol[p.size()-1] = 0.0;
for(int idx = 1; idx < p.size()-1; ++idx)
{
_bCol[idx+1] = _bCol[idx+1] - _bCol[idx]*_offDiagElems[idx]/_diagElems[idx];
_diagElems[idx+1] = _diagElems[idx+1] - _offDiagElems[idx]*_offDiagElems[idx]/_diagElems[idx];
}
for(int idx = (int)p.size()-2; idx > 0; --idx)
{
_xCol[idx] = (_bCol[idx] - _offDiagElems[idx]*_xCol[idx+1])/_diagElems[idx];
}
return true;
}
};
/* Bezier Spline Implementation
* Based on this article:
* http://www.particleincell.com/blog/2012/bezier-splines/
*/
class BezierSpine : public SplineBase
{
private:
vector<Vec2> _p1Points;
vector<Vec2> _p2Points;
public:
BezierSpine()
{
_p1Points.reserve(NOM_SIZE);
_p2Points.reserve(NOM_SIZE);
}
/* Evaluate the spline for the ith segment
* for parameter. The value of parameter t must
* be between 0 and 1.
*/
inline virtual Vec2 Eval(int seg, double t)
{
assert(seg < _p1Points.size());
assert(seg < _p2Points.size());
double omt = 1.0 - t;
Vec2 p0 = GetPoints()[seg];
Vec2 p1 = _p1Points[seg];
Vec2 p2 = _p2Points[seg];
Vec2 p3 = GetPoints()[seg+1];
double xVal = omt*omt*omt*p0.x + 3*omt*omt*t*p1.x +3*omt*t*t*p2.x+t*t*t*p3.x;
double yVal = omt*omt*omt*p0.y + 3*omt*omt*t*p1.y +3*omt*t*t*p2.y+t*t*t*p3.y;
return Vec2(xVal,yVal);
}
/* Clear out all the data.
*/
virtual void ResetDerived()
{
_p1Points.clear();
_p2Points.clear();
}
virtual bool ComputeSpline()
{
const vector<Vec2>& p = GetPoints();
int N = (int)p.size()-1;
_p1Points.resize(N);
_p2Points.resize(N);
if(N == 0)
return false;
if(N == 1)
{ // Only 2 points...just create a straight line.
// Constraint: 3*P1 = 2*P0 + P3
_p1Points[0] = (2.0/3.0*p[0] + 1.0/3.0*p[1]);
// Constraint: P2 = 2*P1 - P0
_p2Points[0] = 2.0*_p1Points[0] - p[0];
return true;
}
/*rhs vector*/
vector<Vec2> a(N);
vector<Vec2> b(N);
vector<Vec2> c(N);
vector<Vec2> r(N);
/*left most segment*/
a[0].x = 0;
b[0].x = 2;
c[0].x = 1;
r[0].x = p[0].x+2*p[1].x;
a[0].y = 0;
b[0].y = 2;
c[0].y = 1;
r[0].y = p[0].y+2*p[1].y;
/*internal segments*/
for (int i = 1; i < N - 1; i++)
{
a[i].x=1;
b[i].x=4;
c[i].x=1;
r[i].x = 4 * p[i].x + 2 * p[i+1].x;
a[i].y=1;
b[i].y=4;
c[i].y=1;
r[i].y = 4 * p[i].y + 2 * p[i+1].y;
}
/*right segment*/
a[N-1].x = 2;
b[N-1].x = 7;
c[N-1].x = 0;
r[N-1].x = 8*p[N-1].x+p[N].x;
a[N-1].y = 2;
b[N-1].y = 7;
c[N-1].y = 0;
r[N-1].y = 8*p[N-1].y+p[N].y;
/*solves Ax=b with the Thomas algorithm (from Wikipedia)*/
for (int i = 1; i < N; i++)
{
double m;
m = a[i].x/b[i-1].x;
b[i].x = b[i].x - m * c[i - 1].x;
r[i].x = r[i].x - m * r[i-1].x;
m = a[i].y/b[i-1].y;
b[i].y = b[i].y - m * c[i - 1].y;
r[i].y = r[i].y - m * r[i-1].y;
}
_p1Points[N-1].x = r[N-1].x/b[N-1].x;
_p1Points[N-1].y = r[N-1].y/b[N-1].y;
for (int i = N - 2; i >= 0; --i)
{
_p1Points[i].x = (r[i].x - c[i].x * _p1Points[i+1].x) / b[i].x;
_p1Points[i].y = (r[i].y - c[i].y * _p1Points[i+1].y) / b[i].y;
}
/*we have p1, now compute p2*/
for (int i=0;i<N-1;i++)
{
_p2Points[i].x=2*p[i+1].x-_p1Points[i+1].x;
_p2Points[i].y=2*p[i+1].y-_p1Points[i+1].y;
}
_p2Points[N-1].x = 0.5 * (p[N].x+_p1Points[N-1].x);
_p2Points[N-1].y = 0.5 * (p[N].y+_p1Points[N-1].y);
return true;
}
virtual void DumpDerived()
{
cout << " Control Points " << endl;
for(int idx = 0; idx < _p1Points.size(); idx++)
{
cout << "[" << idx << "] ";
cout << "P1: " << _p1Points[idx];
cout << " ";
cout << "P2: " << _p2Points[idx];
cout << endl;
}
}
};
#endif /* defined(__SplineCommon__) */
一些笔记
以下是使用Bezier Spline的示例：
/* Smooth the points on the path so that turns look
* more natural. We'll only smooth the first few
* points. Most of the time, the full path will not
* be executed anyway...why waste cycles.
*/
void SmoothPath(vector<Vec2>& path, int32 divisions)
{
const int SMOOTH_POINTS = 6;
BezierSpine spline;
if(path.size() < 2)
return;
// Cache off the first point. If the first point is removed,
// the we occasionally run into problems if the collision detection
// says the first node is occupied but the splined point is too
// close, so the FSM "spins" trying to find a sensor cell that is
// not occupied.
// Vec2 firstPoint = path.back();
// path.pop_back();
// Grab the points.
for(int idx = 0; idx < SMOOTH_POINTS && path.size() > 0; idx++)
{
spline.AddPoint(path.back());
path.pop_back();
}
// Smooth them.
spline.ComputeSpline();
// Push them back in.
for(int idx = spline.GetPoints().size()-2; idx >= 0; --idx)
{
for(int division = divisions-1; division >= 0; --division)
{
double t = division*1.0/divisions;
path.push_back(spline.Eval(idx, t));
}
}
// Push back in the original first point.
// path.push_back(firstPoint);
}
备注
此代码是更大代码库but you can download it all on github和see a blog entry about it here的一部分。
You can look at this in action in this video.
这有用吗？