ORB-SLAM2的原始碼閱讀(二):ORB特徵提取
阿新 • • 發佈:2019-02-04
怎麼讀一個工程?程式碼菜鳥不敢妄言。LZ也就嘗試化整為零,逐個擊破,再化零為整,全域性理解。下面程式碼來自ORB_SLAM2的ORBextractor.h和ORBextractor.cc.為什麼要寫這個部落格,因為笨,看程式碼怕忘了。自己寫一遍加深下記憶。為什麼不直接轉載?大神很多,轉載自己思考很少,自己動手雖然比不過大神,但是還是會有所收穫。如果有好的,可以把連結加在參考部落格位置。
#ifndef ORBEXTRACTOR_H
#define ORBEXTRACTOR_H
#include <vector>
#include <list>
#include <opencv/cv.h>
namespace ORB_SLAM2
{
class ExtractorNode
{
public:
ExtractorNode():bNoMore(false){}
void DivideNode(ExtractorNode &n1, ExtractorNode &n2, ExtractorNode &n3, ExtractorNode &n4);
std::vector<cv::KeyPoint> vKeys;
cv::Point2i UL, UR, BL, BR;
std::list<ExtractorNode> ::iterator lit;
bool bNoMore;
};
class ORBextractor
{
public:
enum {HARRIS_SCORE=0, FAST_SCORE=1 };
ORBextractor(int nfeatures, float scaleFactor, int nlevels,
int iniThFAST, int minThFAST);
~ORBextractor(){}
// Compute the ORB features and descriptors on an image.
// ORB are dispersed on the image using an octree.
// Mask is ignored in the current implementation.
void operator()( cv::InputArray image, cv::InputArray mask,
std::vector<cv::KeyPoint>& keypoints,
cv::OutputArray descriptors);
int inline GetLevels(){
return nlevels;}
float inline GetScaleFactor(){
return scaleFactor;}
std::vector<float> inline GetScaleFactors(){
return mvScaleFactor;
}
std::vector<float> inline GetInverseScaleFactors(){
return mvInvScaleFactor;
}
std::vector<float> inline GetScaleSigmaSquares(){
return mvLevelSigma2;
}
std::vector<float> inline GetInverseScaleSigmaSquares(){
return mvInvLevelSigma2;
}
std::vector<cv::Mat> mvImagePyramid;
protected:
void ComputePyramid(cv::Mat image);
void ComputeKeyPointsOctTree(std::vector<std::vector<cv::KeyPoint> >& allKeypoints);
std::vector<cv::KeyPoint> DistributeOctTree(const std::vector<cv::KeyPoint>& vToDistributeKeys, const int &minX,
const int &maxX, const int &minY, const int &maxY, const int &nFeatures, const int &level);
void ComputeKeyPointsOld(std::vector<std::vector<cv::KeyPoint> >& allKeypoints);
std::vector<cv::Point> pattern;
int nfeatures;
double scaleFactor;
int nlevels;
int iniThFAST;
int minThFAST;
std::vector<int> mnFeaturesPerLevel;
std::vector<int> umax;
std::vector<float> mvScaleFactor;
std::vector<float> mvInvScaleFactor;
std::vector<float> mvLevelSigma2;
std::vector<float> mvInvLevelSigma2;
};
} //namespace ORB_SLAM
#endif
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/features2d/features2d.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <vector>
#include "ORBextractor.h"
using namespace cv;
using namespace std;
namespace ORB_SLAM2
{
const int PATCH_SIZE = 31; //塊的大小為31
const int HALF_PATCH_SIZE = 15; //一半塊的大小為15
const int EDGE_THRESHOLD = 19; //邊界的閾值為19
static float IC_Angle(const Mat& image, Point2f pt, const vector<int> & u_max)
{
int m_01 = 0, m_10 = 0; //根據公式初始化影象塊的矩
const uchar* center = &image.at<uchar> (cvRound(pt.y), cvRound(pt.x));
// Treat the center line differently, v=0
for (int u = -HALF_PATCH_SIZE; u <= HALF_PATCH_SIZE; ++u)
m_10 += u * center[u];
// Go line by line in the circuI853lar patch
int step = (int)image.step1(); // 每行含有的元素個數
for (int v = 1; v <= HALF_PATCH_SIZE; ++v)
{
// Proceed over the two lines
// 每次處理對稱的兩行
int v_sum = 0;
int d = u_max[v];
for (int u = -d; u <= d; ++u)
{
int val_plus = center[u + v*step], val_minus = center[u - v*step];
v_sum += (val_plus - val_minus); //因為val_minus對應的是-v,為了統一符號,用減法
m_10 += u * (val_plus + val_minus);
}
m_01 += v * v_sum;
}
//返回計算的角度
return fastAtan2((float)m_01, (float)m_10);
}
//弧度制和角度制之間的轉換
const float factorPI = (float)(CV_PI/180.f);
//計算ORB描述子
static void computeOrbDescriptor(const KeyPoint& kpt,
const Mat& img, const Point* pattern,
uchar* desc)
{
float angle = (float)kpt.angle*factorPI;
float a = (float)cos(angle), b = (float)sin(angle);
const uchar* center = &img.at<uchar>(cvRound(kpt.pt.y), cvRound(kpt.pt.x));
const int step = (int)img.step;
#define GET_VALUE(idx) \
center[cvRound(pattern[idx].x*b + pattern[idx].y*a)*step + \
cvRound(pattern[idx].x*a - pattern[idx].y*b)]
for (int i = 0; i < 32; ++i, pattern += 16)
{
int t0, t1, val;
t0 = GET_VALUE(0); t1 = GET_VALUE(1);
val = t0 < t1;
t0 = GET_VALUE(2); t1 = GET_VALUE(3);
val |= (t0 < t1) << 1;
t0 = GET_VALUE(4); t1 = GET_VALUE(5);
val |= (t0 < t1) << 2;
t0 = GET_VALUE(6); t1 = GET_VALUE(7);
val |= (t0 < t1) << 3;
t0 = GET_VALUE(8); t1 = GET_VALUE(9);
val |= (t0 < t1) << 4;
t0 = GET_VALUE(10); t1 = GET_VALUE(11);
val |= (t0 < t1) << 5;
t0 = GET_VALUE(12); t1 = GET_VALUE(13);
val |= (t0 < t1) << 6;
t0 = GET_VALUE(14); t1 = GET_VALUE(15);
val |= (t0 < t1) << 7;
desc[i] = (uchar)val;
}
#undef GET_VALUE
}
//計算描述子的pattern,高斯分佈,也可以使用其他定義的pattern
static int bit_pattern_31_[256*4] =
{
8,-3, 9,5/*mean (0), correlation (0)*/,
4,2, 7,-12/*mean (1.12461e-05), correlation (0.0437584)*/,
-11,9, -8,2/*mean (3.37382e-05), correlation (0.0617409)*/,
7,-12, 12,-13/*mean (5.62303e-05), correlation (0.0636977)*/,
2,-13, 2,12/*mean (0.000134953), correlation (0.085099)*/,
1,-7, 1,6/*mean (0.000528565), correlation (0.0857175)*/,
-2,-10, -2,-4/*mean (0.0188821), correlation (0.0985774)*/,
-13,-13, -11,-8/*mean (0.0363135), correlation (0.0899616)*/,
-13,-3, -12,-9/*mean (0.121806), correlation (0.099849)*/,
10,4, 11,9/*mean (0.122065), correlation (0.093285)*/,
-13,-8, -8,-9/*mean (0.162787), correlation (0.0942748)*/,
-11,7, -9,12/*mean (0.21561), correlation (0.0974438)*/,
7,7, 12,6/*mean (0.160583), correlation (0.130064)*/,
-4,-5, -3,0/*mean (0.228171), correlation (0.132998)*/,
-13,2, -12,-3/*mean (0.00997526), correlation (0.145926)*/,
-9,0, -7,5/*mean (0.198234), correlation (0.143636)*/,
12,-6, 12,-1/*mean (0.0676226), correlation (0.16689)*/,
-3,6, -2,12/*mean (0.166847), correlation (0.171682)*/,
-6,-13, -4,-8/*mean (0.101215), correlation (0.179716)*/,
11,-13, 12,-8/*mean (0.200641), correlation (0.192279)*/,
4,7, 5,1/*mean (0.205106), correlation (0.186848)*/,
5,-3, 10,-3/*mean (0.234908), correlation (0.192319)*/,
3,-7, 6,12/*mean (0.0709964), correlation (0.210872)*/,
-8,-7, -6,-2/*mean (0.0939834), correlation (0.212589)*/,
-2,11, -1,-10/*mean (0.127778), correlation (0.20866)*/,
-13,12, -8,10/*mean (0.14783), correlation (0.206356)*/,
-7,3, -5,-3/*mean (0.182141), correlation (0.198942)*/,
-4,2, -3,7/*mean (0.188237), correlation (0.21384)*/,
-10,-12, -6,11/*mean (0.14865), correlation (0.23571)*/,
5,-12, 6,-7/*mean (0.222312), correlation (0.23324)*/,
5,-6, 7,-1/*mean (0.229082), correlation (0.23389)*/,
1,0, 4,-5/*mean (0.241577), correlation (0.215286)*/,
9,11, 11,-13/*mean (0.00338507), correlation (0.251373)*/,
4,7, 4,12/*mean (0.131005), correlation (0.257622)*/,
2,-1, 4,4/*mean (0.152755), correlation (0.255205)*/,
-4,-12, -2,7/*mean (0.182771), correlation (0.244867)*/,
-8,-5, -7,-10/*mean (0.186898), correlation (0.23901)*/,
4,11, 9,12/*mean (0.226226), correlation (0.258255)*/,
0,-8, 1,-13/*mean (0.0897886), correlation (0.274827)*/,
-13,-2, -8,2/*mean (0.148774), correlation (0.28065)*/,
-3,-2, -2,3/*mean (0.153048), correlation (0.283063)*/,
-6,9, -4,-9/*mean (0.169523), correlation (0.278248)*/,
8,12, 10,7/*mean (0.225337), correlation (0.282851)*/,
0,9, 1,3/*mean (0.226687), correlation (0.278734)*/,
7,-5, 11,-10/*mean (0.00693882), correlation (0.305161)*/,
-13,-6, -11,0/*mean (0.0227283), correlation (0.300181)*/,
10,7, 12,1/*mean (0.125517), correlation (0.31089)*/,
-6,-3, -6,12/*mean (0.131748), correlation (0.312779)*/,
10,-9, 12,-4/*mean (0.144827), correlation (0.292797)*/,
-13,8, -8,-12/*mean (0.149202), correlation (0.308918)*/,
-13,0, -8,-4/*mean (0.160909), correlation (0.310013)*/,
3,3, 7,8/*mean (0.177755), correlation (0.309394)*/,
5,7, 10,-7/*mean (0.212337), correlation (0.310315)*/,
-1,7, 1,-12/*mean (0.214429), correlation (0.311933)*/,
3,-10, 5,6/*mean (0.235807), correlation (0.313104)*/,
2,-4, 3,-10/*mean (0.00494827), correlation (0.344948)*/,
-13,0, -13,5/*mean (0.0549145), correlation (0.344675)*/,
-13,-7, -12,12/*mean (0.103385), correlation (0.342715)*/,
-13,3, -11,8/*mean (0.134222), correlation (0.322922)*/,
-7,12, -4,7/*mean (0.153284), correlation (0.337061)*/,
6,-10, 12,8/*mean (0.154881), correlation (0.329257)*/,
-9,-1, -7,-6/*mean (0.200967), correlation (0.33312)*/,
-2,-5, 0,12/*mean (0.201518), correlation (0.340635)*/,
-12,5, -7,5/*mean (0.207805), correlation (0.335631)*/,
3,-10, 8,-13/*mean (0.224438), correlation (0.34504)*/,
-7,-7, -4,5/*mean (0.239361), correlation (0.338053)*/,
-3,-2, -1,-7/*mean (0.240744), correlation (0.344322)*/,
2,9, 5,-11/*mean (0.242949), correlation (0.34145)*/,
-11,-13, -5,-13/*mean (0.244028), correlation (0.336861)*/,
-1,6, 0,-1/*mean (0.247571), correlation (0.343684)*/,
5,-3, 5,2/*mean (0.000697256), correlation (0.357265)*/,
-4,-13, -4,12/*mean (0.00213675), correlation (0.373827)*/,
-9,-6, -9,6/*mean (0.0126856), correlation (0.373938)*/,
-12,-10, -8,-4/*mean (0.0152497), correlation (0.364237)*/,
10,2, 12,-3/*mean (0.0299933), correlation (0.345292)*/,
7,12, 12,12/*mean (0.0307242), correlation (0.366299)*/,
-7,-13, -6,5/*mean (0.0534975), correlation (0.368357)*/,
-4,9, -3,4/*mean (0.099865), correlation (0.372276)*/,
7,-1, 12,2/*mean (0.117083), correlation (0.364529)*/,
-7,6, -5,1/*mean (0.126125), correlation (0.369606)*/,
-13,11, -12,5/*mean (0.130364), correlation (0.358502)*/,
-3,7, -2,-6/*mean (0.131691), correlation (0.375531)*/,
7,-8, 12,-7/*mean (0.160166), correlation (0.379508)*/,
-13,-7, -11,-12/*mean (0.167848), correlation (0.353343)*/,
1,-3, 12,12/*mean (0.183378), correlation (0.371916)*/,
2,-6, 3,0/*mean (0.228711), correlation (0.371761)*/,
-4,3, -2,-13/*mean (0.247211), correlation (0.364063)*/,
-1,-13, 1,9/*mean (0.249325), correlation (0.378139)*/,
7,1, 8,-6/*mean (0.000652272), correlation (0.411682)*/,
1,-1, 3,12/*mean (0.00248538), correlation (0.392988)*/,
9,1, 12,6/*mean (0.0206815), correlation (0.386106)*/,
-1,-9, -1,3/*mean (0.0364485), correlation (0.410752)*/,
-13,-13, -10,5/*mean (0.0376068), correlation (0.398374)*/,
7,7, 10,12/*mean (0.0424202), correlation (0.405663)*/,
12,-5, 12,9/*mean (0.0942645), correlation (0.410422)*/,
6,3, 7,11/*mean (0.1074), correlation (0.413224)*/,
5,-13, 6,10/*mean (0.109256), correlation (0.408646)*/,
2,-12, 2,3/*mean (0.131691), correlation (0.416076)*/,
3,8, 4,-6/*mean (0.165081), correlation (0.417569)*/,
2,6, 12,-13/*mean (0.171874), correlation (0.408471)*/,
9,-12, 10,3/*mean (0.175146), correlation (0.41296)*/,
-8,4, -7,9/*mean (0.183682), correlation (0.402956)*/,
-11,12, -4,-6/*mean (0.184672), correlation (0.416125)*/,
1,12, 2,-8/*mean (0.191487), correlation (0.386696)*/,
6,-9, 7,-4/*mean (0.192668), correlation (0.394771)*/,
2,3, 3,-2/*mean (0.200157), correlation (0.408303)*/,
6,3, 11,0/*mean (0.204588), correlation (0.411762)*/,
3,-3, 8,-8/*mean (0.205904), correlation (0.416294)*/,
7,8, 9,3/*mean (0.213237), correlation (0.409306)*/,
-11,-5, -6,-4/*mean (0.243444), correlation (0.395069)*/,
-10,11, -5,10/*mean (0.247672), correlation (0.413392)*/,
-5,-8, -3,12/*mean (0.24774), correlation (0.411416)*/,
-10,5, -9,0/*mean (0.00213675), correlation (0.454003)*/,
8,-1, 12,-6/*mean (0.0293635), correlation (0.455368)*/,
4,-6, 6,-11/*mean (0.0404971), correlation (0.457393)*/,
-10,12, -8,7/*mean (0.0481107), correlation (0.448364)*/,
4,-2, 6,7/*mean (0.050641), correlation (0.455019)*/,
-2,0, -2,12/*mean (0.0525978), correlation (0.44338)*/,
-5,-8, -5,2/*mean (0.0629667), correlation (0.457096)*/,
7,-6, 10,12/*mean (0.0653846), correlation (0.445623)*/,
-9,-13, -8,-8/*mean (0.0858749), correlation (0.449789)*/,
-5,-13, -5,-2/*mean (0.122402), correlation (0.450201)*/,
8,-8, 9,-13/*mean (0.125416), correlation (0.453224)*/,
-9,-11, -9,0/*mean (0.130128), correlation (0.458724)*/,
1,-8, 1,-2/*mean (0.132467), correlation (0.440133)*/,
7,-4, 9,1/*mean (0.132692), correlation (0.454)*/,
-2,1, -1,-4/*mean (0.135695), correlation (0.455739)*/,
11,-6, 12,-11/*mean (0.142904), correlation (0.446114)*/,
-12,-9, -6,4/*mean (0.146165), correlation (0.451473)*/,
3,7, 7,12/*mean (0.147627), correlation (0.456643)*/,
5,5, 10,8/*mean (0.152901), correlation (0.455036)*/,
0,-4, 2,8/*mean (0.167083), correlation (0.459315)*/,
-9,12, -5,-13/*mean (0.173234), correlation (0.454706)*/,
0,7, 2,12/*mean (0.18312), correlation (0.433855)*/,
-1,2, 1,7/*mean (0.185504), correlation (0.443838)*/,
5,11, 7,-9/*mean (0.185706), correlation (0.451123)*/,
3,5, 6,-8/*mean (0.188968), correlation (0.455808)*/,
-13,-4, -8,9/*mean (0.191667), correlation (0.459128)*/,
-5,9, -3,-3/*mean (0.193196), correlation (0.458364)*/,
-4,-7, -3,-12/*mean (0.196536), correlation (0.455782)*/,
6,5, 8,0/*mean (0.1972), correlation (0.450481)*/,
-7,6, -6,12/*mean (0.199438), correlation (0.458156)*/,
-13,6, -5,-2/*mean (0.211224), correlation (0.449548)*/,
1,-10, 3,10/*mean (0.211718), correlation (0.440606)*/,
4,1, 8,-4/*mean (0.213034), correlation (0.443177)*/,
-2,-2, 2,-13/*mean (0.234334), correlation (0.455304)*/,
2,-12, 12,12/*mean (0.235684), correlation (0.443436)*/,
-2,-13, 0,-6/*mean (0.237674), correlation (0.452525)*/,
4,1, 9,3/*mean (0.23962), correlation (0.444824)*/,
-6,-10, -3,-5/*mean (0.248459), correlation (0.439621)*/,
-3,-13, -1,1/*mean (0.249505), correlation (0.456666)*/,
7,5, 12,-11/*mean (0.00119208), correlation (0.495466)*/,
4,-2, 5,-7/*mean (0.00372245), correlation (0.484214)*/,
-13,9, -9,-5/*mean (0.00741116), correlation (0.499854)*/,
7,1, 8,6/*mean (0.0208952), correlation (0.499773)*/,
7,-8, 7,6/*mean (0.0220085), correlation (0.501609)*/,
-7,-4, -7,1/*mean (0.0233806), correlation (0.496568)*/,
-8,11, -7,-8/*mean (0.0236505), correlation (0.489719)*/,
-13,6, -12,-8/*mean (0.0268781), correlation (0.503487)*/,
2,4, 3,9/*mean (0.0323324), correlation (0.501938)*/,
10,-5, 12,3/*mean (0.0399235), correlation (0.494029)*/,
-6,-5, -6,7/*mean (0.0420153), correlation (0.486579)*/,
8,-3, 9,-8/*mean (0.0548021), correlation (0.484237)*/,
2,-12, 2,8/*mean (0.0616622), correlation (0.496642)*/,
-11,-2, -10,3/*mean (0.0627755), correlation (0.498563)*/,
-12,-13, -7,-9/*mean (0.0829622), correlation (0.495491)*/,
-11,0, -10,-5/*mean (0.0843342), correlation (0.487146)*/,
5,-3, 11,8/*mean (0.0929937), correlation (0.502315)*/,
-2,-13, -1,12/*mean (0.113327), correlation (0.48941)*/,
-1,-8, 0,9/*mean (0.132119), correlation (0.467268)*/,
-13,-11, -12,-5/*mean (0.136269), correlation (0.498771)*/,
-10,-2, -10,11/*mean (0.142173), correlation (0.498714)*/,
-3,9, -2,-13/*mean (0.144141), correlation (0.491973)*/,
2,-3, 3,2/*mean (0.14892), correlation (0.500782)*/,
-9,-13, -4,0/*mean (0.150371), correlation (0.498211)*/,
-4,6, -3,-10/*mean (0.152159), correlation (0.495547)*/,
-4,12, -2,-7/*mean (0.156152), correlation (0.496925)*/,
-6,-11, -4,9/*mean (0.15749), correlation (0.499222)*/,
6,-3, 6,11/*mean (0.159211), correlation (0.503821)*/,
-13,11, -5,5/*mean (0.162427), correlation (0.501907)*/,
11,11, 12,6/*mean (0.16652), correlation (0.497632)*/,
7,-5, 12,-2/*mean (0.169141), correlation (0.484474)*/,
-1,12, 0,7/*mean (0.169456), correlation (0.495339)*/,
-4,-8, -3,-2/*mean (0.171457), correlation (0.487251)*/,
-7,1, -6,7/*mean (0.175), correlation (0.500024)*/,
-13,-12, -8,-13/*mean (0.175866), correlation (0.497523)*/,
-7,-2, -6,-8/*mean (0.178273), correlation (0.501854)*/,
-8,5, -6,-9/*mean (0.181107), correlation (0.494888)*/,
-5,-1, -4,5/*mean (0.190227), correlation (0.482557)*/,
-13,7, -8,10/*mean (0.196739), correlation (0.496503)*/,
1,5, 5,-13/*mean (0.19973), correlation (0.499759)*/,
1,0, 10,-13/*mean (0.204465), correlation (0.49873)*/,
9,12, 10,-1/*mean (0.209334), correlation (0.49063)*/,
5,-8, 10,-9/*mean (0.211134), correlation (0.503011)*/,
-1,11, 1,-13/*mean (0.212), correlation (0.499414)*/,
-9,-3, -6,2/*mean (0.212168), correlation (0.480739)*/,
-1,-10, 1,12/*mean (0.212731), correlation (0.502523)*/,
-13,1, -8,-10/*mean (0.21327), correlation (0.489786)*/,
8,-11, 10,-6/*mean (0.214159), correlation (0.488246)*/,
2,-13, 3,-6/*mean (0.216993), correlation (0.50287)*/,
7,-13, 12,-9/*mean (0.223639), correlation (0.470502)*/,
-10,-10, -5,-7/*mean (0.224089), correlation (0.500852)*/,
-10,-8, -8,-13/*mean (0.228666), correlation (0.502629)*/,
4,-6, 8,5/*mean (0.22906), correlation (0.498305)*/,
3,12, 8,-13/*mean (0.233378), correlation (0.503825)*/,
-4,2, -3,-3/*mean (0.234323), correlation (0.476692)*/,
5,-13, 10,-12/*mean (0.236392), correlation (0.475462)*/,
4,-13, 5,-1/*mean (0.236842), correlation (0.504132)*/,
-9,9, -4,3/*mean (0.236977), correlation (0.497739)*/,
0,3, 3,-9/*mean (0.24314), correlation (0.499398)*/,
-12,1, -6,1/*mean (0.243297), correlation (0.489447)*/,
3,2, 4,-8/*mean (0.00155196), correlation (0.553496)*/,
-10,-10, -10,9/*mean (0.00239541), correlation (0.54297)*/,
8,-13, 12,12/*mean (0.0034413), correlation (0.544361)*/,
-8,-12, -6,-5/*mean (0.003565), correlation (0.551225)*/,
2,2, 3,7/*mean (0.00835583), correlation (0.55285)*/,
10,6, 11,-8/*mean (0.00885065), correlation (0.540913)*/,
6,8, 8,-12/*mean (0.0101552), correlation (0.551085)*/,
-7,10, -6,5/*mean (0.0102227), correlation (0.533635)*/,
-3,-9, -3,9/*mean (0.0110211), correlation (0.543121)*/,
-1,-13, -1,5/*mean (0.0113473), correlation (0.550173)*/,
-3,-7, -3,4/*mean (0.0140913