自己动手写ORB特征
通过一些简单的算法修改，使ORB的提取效率加速了5.8倍。编译该程序需要CPU支持SSE指令集。
如果我们能够对特征提取部分进一步并行化处理，则算法还可以有加速的空间。
//
// Created by xiang on 18-11-25.
// #include <opencv2/opencv.hpp>
#include <string>
#include <nmmintrin.h>
#include <chrono> using namespace std; // global variables
string first_file = "./1.png";
string second_file = "./2.png"; // 32 bit unsigned int, will have 8, 8x32=256
typedef vector<uint32_t> DescType; // Descriptor type /**
* compute descriptor of orb keypoints
* @param img input image
* @param keypoints detected fast keypoints
* @param descriptors descriptors
*
* NOTE: if a keypoint goes outside the image boundary (8 pixels), descriptors will not be computed and will be left as
* empty
*/
void ComputeORB(const cv::Mat &img, vector<cv::KeyPoint> &keypoints, vector<DescType> &descriptors); /**
* brute-force match two sets of descriptors
* @param desc1 the first descriptor
* @param desc2 the second descriptor
* @param matches matches of two images
*/
void BfMatch(const vector<DescType> &desc1, const vector<DescType> &desc2, vector<cv::DMatch> &matches); int main(int argc, char **argv) { // load image
cv::Mat first_image = cv::imread(first_file, );
cv::Mat second_image = cv::imread(second_file, );
assert(first_image.data != nullptr && second_image.data != nullptr); // detect FAST keypoints1 using threshold=40
chrono::steady_clock::time_point t1 = chrono::steady_clock::now();
vector<cv::KeyPoint> keypoints1;
cv::FAST(first_image, keypoints1, );
vector<DescType> descriptor1;
ComputeORB(first_image, keypoints1, descriptor1); // same for the second
vector<cv::KeyPoint> keypoints2;
vector<DescType> descriptor2;
cv::FAST(second_image, keypoints2, );
ComputeORB(second_image, keypoints2, descriptor2);
chrono::steady_clock::time_point t2 = chrono::steady_clock::now();
chrono::duration<double> time_used = chrono::duration_cast<chrono::duration<double>>(t2 - t1);
cout << "extract ORB cost = " << time_used.count() << " seconds. " << endl; // find matches
vector<cv::DMatch> matches;
t1 = chrono::steady_clock::now();
BfMatch(descriptor1, descriptor2, matches);
t2 = chrono::steady_clock::now();
time_used = chrono::duration_cast<chrono::duration<double>>(t2 - t1);
cout << "match ORB cost = " << time_used.count() << " seconds. " << endl;
cout << "matches: " << matches.size() << endl; // plot the matches
cv::Mat image_show;
cv::drawMatches(first_image, keypoints1, second_image, keypoints2, matches, image_show);
cv::imshow("matches", image_show);
cv::imwrite("matches.png", image_show);
cv::waitKey(); cout << "done." << endl;
return ;
} // -------------------------------------------------------------------------------------------------- //
// ORB pattern
int ORB_pattern[ * ] = {
, -, , /*mean (0), correlation (0)*/,
, , , -/*mean (1.12461e-05), correlation (0.0437584)*/,
-, , -, /*mean (3.37382e-05), correlation (0.0617409)*/,
, -, , -/*mean (5.62303e-05), correlation (0.0636977)*/,
, -, , /*mean (0.000134953), correlation (0.085099)*/,
, -, , /*mean (0.000528565), correlation (0.0857175)*/,
-, -, -, -/*mean (0.0188821), correlation (0.0985774)*/,
-, -, -, -/*mean (0.0363135), correlation (0.0899616)*/,
-, -, -, -/*mean (0.121806), correlation (0.099849)*/,
, , , /*mean (0.122065), correlation (0.093285)*/,
-, -, -, -/*mean (0.162787), correlation (0.0942748)*/,
-, , -, /*mean (0.21561), correlation (0.0974438)*/,
, , , /*mean (0.160583), correlation (0.130064)*/,
-, -, -, /*mean (0.228171), correlation (0.132998)*/,
-, , -, -/*mean (0.00997526), correlation (0.145926)*/,
-, , -, /*mean (0.198234), correlation (0.143636)*/,
, -, , -/*mean (0.0676226), correlation (0.16689)*/,
-, , -, /*mean (0.166847), correlation (0.171682)*/,
-, -, -, -/*mean (0.101215), correlation (0.179716)*/,
, -, , -/*mean (0.200641), correlation (0.192279)*/,
, , , /*mean (0.205106), correlation (0.186848)*/,
, -, , -/*mean (0.234908), correlation (0.192319)*/,
, -, , /*mean (0.0709964), correlation (0.210872)*/,
-, -, -, -/*mean (0.0939834), correlation (0.212589)*/,
-, , -, -/*mean (0.127778), correlation (0.20866)*/,
-, , -, /*mean (0.14783), correlation (0.206356)*/,
-, , -, -/*mean (0.182141), correlation (0.198942)*/,
-, , -, /*mean (0.188237), correlation (0.21384)*/,
-, -, -, /*mean (0.14865), correlation (0.23571)*/,
, -, , -/*mean (0.222312), correlation (0.23324)*/,
, -, , -/*mean (0.229082), correlation (0.23389)*/,
, , , -/*mean (0.241577), correlation (0.215286)*/,
, , , -/*mean (0.00338507), correlation (0.251373)*/,
, , , /*mean (0.131005), correlation (0.257622)*/,
, -, , /*mean (0.152755), correlation (0.255205)*/,
-, -, -, /*mean (0.182771), correlation (0.244867)*/,
-, -, -, -/*mean (0.186898), correlation (0.23901)*/,
, , , /*mean (0.226226), correlation (0.258255)*/,
, -, , -/*mean (0.0897886), correlation (0.274827)*/,
-, -, -, /*mean (0.148774), correlation (0.28065)*/,
-, -, -, /*mean (0.153048), correlation (0.283063)*/,
-, , -, -/*mean (0.169523), correlation (0.278248)*/,
, , , /*mean (0.225337), correlation (0.282851)*/,
, , , /*mean (0.226687), correlation (0.278734)*/,
, -, , -/*mean (0.00693882), correlation (0.305161)*/,
-, -, -, /*mean (0.0227283), correlation (0.300181)*/,
, , , /*mean (0.125517), correlation (0.31089)*/,
-, -, -, /*mean (0.131748), correlation (0.312779)*/,
, -, , -/*mean (0.144827), correlation (0.292797)*/,
-, , -, -/*mean (0.149202), correlation (0.308918)*/,
-, , -, -/*mean (0.160909), correlation (0.310013)*/,
, , , /*mean (0.177755), correlation (0.309394)*/,
, , , -/*mean (0.212337), correlation (0.310315)*/,
-, , , -/*mean (0.214429), correlation (0.311933)*/,
, -, , /*mean (0.235807), correlation (0.313104)*/,
, -, , -/*mean (0.00494827), correlation (0.344948)*/,
-, , -, /*mean (0.0549145), correlation (0.344675)*/,
-, -, -, /*mean (0.103385), correlation (0.342715)*/,
-, , -, /*mean (0.134222), correlation (0.322922)*/,
-, , -, /*mean (0.153284), correlation (0.337061)*/,
, -, , /*mean (0.154881), correlation (0.329257)*/,
-, -, -, -/*mean (0.200967), correlation (0.33312)*/,
-, -, , /*mean (0.201518), correlation (0.340635)*/,
-, , -, /*mean (0.207805), correlation (0.335631)*/,
, -, , -/*mean (0.224438), correlation (0.34504)*/,
-, -, -, /*mean (0.239361), correlation (0.338053)*/,
-, -, -, -/*mean (0.240744), correlation (0.344322)*/,
, , , -/*mean (0.242949), correlation (0.34145)*/,
-, -, -, -/*mean (0.244028), correlation (0.336861)*/,
-, , , -/*mean (0.247571), correlation (0.343684)*/,
, -, , /*mean (0.000697256), correlation (0.357265)*/,
-, -, -, /*mean (0.00213675), correlation (0.373827)*/,
-, -, -, /*mean (0.0126856), correlation (0.373938)*/,
-, -, -, -/*mean (0.0152497), correlation (0.364237)*/,
, , , -/*mean (0.0299933), correlation (0.345292)*/,
, , , /*mean (0.0307242), correlation (0.366299)*/,
-, -, -, /*mean (0.0534975), correlation (0.368357)*/,
-, , -, /*mean (0.099865), correlation (0.372276)*/,
, -, , /*mean (0.117083), correlation (0.364529)*/,
-, , -, /*mean (0.126125), correlation (0.369606)*/,
-, , -, /*mean (0.130364), correlation (0.358502)*/,
-, , -, -/*mean (0.131691), correlation (0.375531)*/,
, -, , -/*mean (0.160166), correlation (0.379508)*/,
-, -, -, -/*mean (0.167848), correlation (0.353343)*/,
, -, , /*mean (0.183378), correlation (0.371916)*/,
, -, , /*mean (0.228711), correlation (0.371761)*/,
-, , -, -/*mean (0.247211), correlation (0.364063)*/,
-, -, , /*mean (0.249325), correlation (0.378139)*/,
, , , -/*mean (0.000652272), correlation (0.411682)*/,
, -, , /*mean (0.00248538), correlation (0.392988)*/,
, , , /*mean (0.0206815), correlation (0.386106)*/,
-, -, -, /*mean (0.0364485), correlation (0.410752)*/,
-, -, -, /*mean (0.0376068), correlation (0.398374)*/,
, , , /*mean (0.0424202), correlation (0.405663)*/,
, -, , /*mean (0.0942645), correlation (0.410422)*/,
, , , /*mean (0.1074), correlation (0.413224)*/,
, -, , /*mean (0.109256), correlation (0.408646)*/,
, -, , /*mean (0.131691), correlation (0.416076)*/,
, , , -/*mean (0.165081), correlation (0.417569)*/,
, , , -/*mean (0.171874), correlation (0.408471)*/,
, -, , /*mean (0.175146), correlation (0.41296)*/,
-, , -, /*mean (0.183682), correlation (0.402956)*/,
-, , -, -/*mean (0.184672), correlation (0.416125)*/,
, , , -/*mean (0.191487), correlation (0.386696)*/,
, -, , -/*mean (0.192668), correlation (0.394771)*/,
, , , -/*mean (0.200157), correlation (0.408303)*/,
, , , /*mean (0.204588), correlation (0.411762)*/,
, -, , -/*mean (0.205904), correlation (0.416294)*/,
, , , /*mean (0.213237), correlation (0.409306)*/,
-, -, -, -/*mean (0.243444), correlation (0.395069)*/,
-, , -, /*mean (0.247672), correlation (0.413392)*/,
-, -, -, /*mean (0.24774), correlation (0.411416)*/,
-, , -, /*mean (0.00213675), correlation (0.454003)*/,
, -, , -/*mean (0.0293635), correlation (0.455368)*/,
, -, , -/*mean (0.0404971), correlation (0.457393)*/,
-, , -, /*mean (0.0481107), correlation (0.448364)*/,
, -, , /*mean (0.050641), correlation (0.455019)*/,
-, , -, /*mean (0.0525978), correlation (0.44338)*/,
-, -, -, /*mean (0.0629667), correlation (0.457096)*/,
, -, , /*mean (0.0653846), correlation (0.445623)*/,
-, -, -, -/*mean (0.0858749), correlation (0.449789)*/,
-, -, -, -/*mean (0.122402), correlation (0.450201)*/,
, -, , -/*mean (0.125416), correlation (0.453224)*/,
-, -, -, /*mean (0.130128), correlation (0.458724)*/,
, -, , -/*mean (0.132467), correlation (0.440133)*/,
, -, , /*mean (0.132692), correlation (0.454)*/,
-, , -, -/*mean (0.135695), correlation (0.455739)*/,
, -, , -/*mean (0.142904), correlation (0.446114)*/,
-, -, -, /*mean (0.146165), correlation (0.451473)*/,
, , , /*mean (0.147627), correlation (0.456643)*/,
, , , /*mean (0.152901), correlation (0.455036)*/,
, -, , /*mean (0.167083), correlation (0.459315)*/,
-, , -, -/*mean (0.173234), correlation (0.454706)*/,
, , , /*mean (0.18312), correlation (0.433855)*/,
-, , , /*mean (0.185504), correlation (0.443838)*/,
, , , -/*mean (0.185706), correlation (0.451123)*/,
, , , -/*mean (0.188968), correlation (0.455808)*/,
-, -, -, /*mean (0.191667), correlation (0.459128)*/,
-, , -, -/*mean (0.193196), correlation (0.458364)*/,
-, -, -, -/*mean (0.196536), correlation (0.455782)*/,
, , , /*mean (0.1972), correlation (0.450481)*/,
-, , -, /*mean (0.199438), correlation (0.458156)*/,
-, , -, -/*mean (0.211224), correlation (0.449548)*/,
, -, , /*mean (0.211718), correlation (0.440606)*/,
, , , -/*mean (0.213034), correlation (0.443177)*/,
-, -, , -/*mean (0.234334), correlation (0.455304)*/,
, -, , /*mean (0.235684), correlation (0.443436)*/,
-, -, , -/*mean (0.237674), correlation (0.452525)*/,
, , , /*mean (0.23962), correlation (0.444824)*/,
-, -, -, -/*mean (0.248459), correlation (0.439621)*/,
-, -, -, /*mean (0.249505), correlation (0.456666)*/,
, , , -/*mean (0.00119208), correlation (0.495466)*/,
, -, , -/*mean (0.00372245), correlation (0.484214)*/,
-, , -, -/*mean (0.00741116), correlation (0.499854)*/,
, , , /*mean (0.0208952), correlation (0.499773)*/,
, -, , /*mean (0.0220085), correlation (0.501609)*/,
-, -, -, /*mean (0.0233806), correlation (0.496568)*/,
-, , -, -/*mean (0.0236505), correlation (0.489719)*/,
-, , -, -/*mean (0.0268781), correlation (0.503487)*/,
, , , /*mean (0.0323324), correlation (0.501938)*/,
, -, , /*mean (0.0399235), correlation (0.494029)*/,
-, -, -, /*mean (0.0420153), correlation (0.486579)*/,
, -, , -/*mean (0.0548021), correlation (0.484237)*/,
, -, , /*mean (0.0616622), correlation (0.496642)*/,
-, -, -, /*mean (0.0627755), correlation (0.498563)*/,
-, -, -, -/*mean (0.0829622), correlation (0.495491)*/,
-, , -, -/*mean (0.0843342), correlation (0.487146)*/,
, -, , /*mean (0.0929937), correlation (0.502315)*/,
-, -, -, /*mean (0.113327), correlation (0.48941)*/,
-, -, , /*mean (0.132119), correlation (0.467268)*/,
-, -, -, -/*mean (0.136269), correlation (0.498771)*/,
-, -, -, /*mean (0.142173), correlation (0.498714)*/,
-, , -, -/*mean (0.144141), correlation (0.491973)*/,
, -, , /*mean (0.14892), correlation (0.500782)*/,
-, -, -, /*mean (0.150371), correlation (0.498211)*/,
-, , -, -/*mean (0.152159), correlation (0.495547)*/,
-, , -, -/*mean (0.156152), correlation (0.496925)*/,
-, -, -, /*mean (0.15749), correlation (0.499222)*/,
, -, , /*mean (0.159211), correlation (0.503821)*/,
-, , -, /*mean (0.162427), correlation (0.501907)*/,
, , , /*mean (0.16652), correlation (0.497632)*/,
, -, , -/*mean (0.169141), correlation (0.484474)*/,
-, , , /*mean (0.169456), correlation (0.495339)*/,
-, -, -, -/*mean (0.171457), correlation (0.487251)*/,
-, , -, /*mean (0.175), correlation (0.500024)*/,
-, -, -, -/*mean (0.175866), correlation (0.497523)*/,
-, -, -, -/*mean (0.178273), correlation (0.501854)*/,
-, , -, -/*mean (0.181107), correlation (0.494888)*/,
-, -, -, /*mean (0.190227), correlation (0.482557)*/,
-, , -, /*mean (0.196739), correlation (0.496503)*/,
, , , -/*mean (0.19973), correlation (0.499759)*/,
, , , -/*mean (0.204465), correlation (0.49873)*/,
, , , -/*mean (0.209334), correlation (0.49063)*/,
, -, , -/*mean (0.211134), correlation (0.503011)*/,
-, , , -/*mean (0.212), correlation (0.499414)*/,
-, -, -, /*mean (0.212168), correlation (0.480739)*/,
-, -, , /*mean (0.212731), correlation (0.502523)*/,
-, , -, -/*mean (0.21327), correlation (0.489786)*/,
, -, , -/*mean (0.214159), correlation (0.488246)*/,
, -, , -/*mean (0.216993), correlation (0.50287)*/,
, -, , -/*mean (0.223639), correlation (0.470502)*/,
-, -, -, -/*mean (0.224089), correlation (0.500852)*/,
-, -, -, -/*mean (0.228666), correlation (0.502629)*/,
, -, , /*mean (0.22906), correlation (0.498305)*/,
, , , -/*mean (0.233378), correlation (0.503825)*/,
-, , -, -/*mean (0.234323), correlation (0.476692)*/,
, -, , -/*mean (0.236392), correlation (0.475462)*/,
, -, , -/*mean (0.236842), correlation (0.504132)*/,
-, , -, /*mean (0.236977), correlation (0.497739)*/,
, , , -/*mean (0.24314), correlation (0.499398)*/,
-, , -, /*mean (0.243297), correlation (0.489447)*/,
, , , -/*mean (0.00155196), correlation (0.553496)*/,
-, -, -, /*mean (0.00239541), correlation (0.54297)*/,
, -, , /*mean (0.0034413), correlation (0.544361)*/,
-, -, -, -/*mean (0.003565), correlation (0.551225)*/,
, , , /*mean (0.00835583), correlation (0.55285)*/,
, , , -/*mean (0.00885065), correlation (0.540913)*/,
, , , -/*mean (0.0101552), correlation (0.551085)*/,
-, , -, /*mean (0.0102227), correlation (0.533635)*/,
-, -, -, /*mean (0.0110211), correlation (0.543121)*/,
-, -, -, /*mean (0.0113473), correlation (0.550173)*/,
-, -, -, /*mean (0.0140913), correlation (0.554774)*/,
-, -, -, /*mean (0.017049), correlation (0.55461)*/,
, , , /*mean (0.01778), correlation (0.546921)*/,
, -, , /*mean (0.0224022), correlation (0.549667)*/,
, -, , -/*mean (0.029161), correlation (0.546295)*/,
, -, , /*mean (0.0303081), correlation (0.548599)*/,
, -, , /*mean (0.0355151), correlation (0.523943)*/,
-, , -, /*mean (0.0417904), correlation (0.543395)*/,
, -, , /*mean (0.0487292), correlation (0.542818)*/,
, -, , /*mean (0.0575124), correlation (0.554888)*/,
-, -, -, /*mean (0.0594242), correlation (0.544026)*/,
-, , -, /*mean (0.0597391), correlation (0.550524)*/,
-, , -, -/*mean (0.0608974), correlation (0.55383)*/,
, , , -/*mean (0.065126), correlation (0.552006)*/,
, -, , /*mean (0.074224), correlation (0.546372)*/,
-, , -, -/*mean (0.0808592), correlation (0.554875)*/,
-, , -, -/*mean (0.0883378), correlation (0.551178)*/,
-, -, -, -/*mean (0.0901035), correlation (0.548446)*/,
, -, , /*mean (0.0949843), correlation (0.554694)*/,
, , , -/*mean (0.0994152), correlation (0.550979)*/,
-, -, -, -/*mean (0.10045), correlation (0.552714)*/,
, , , -/*mean (0.100686), correlation (0.552594)*/,
, -, , -/*mean (0.101091), correlation (0.532394)*/,
, , , /*mean (0.101147), correlation (0.525576)*/,
-, , , /*mean (0.105263), correlation (0.531498)*/,
, -, , /*mean (0.110785), correlation (0.540491)*/,
-, , -, /*mean (0.112798), correlation (0.536582)*/,
, , , /*mean (0.114181), correlation (0.555793)*/,
, , , -/*mean (0.117431), correlation (0.553763)*/,
, -, , -/*mean (0.118522), correlation (0.553452)*/,
-, , -, /*mean (0.12094), correlation (0.554785)*/,
, , , /*mean (0.122582), correlation (0.555825)*/,
, -, , -/*mean (0.124978), correlation (0.549846)*/,
, , , -/*mean (0.127002), correlation (0.537452)*/,
-, -, , -/*mean (0.127148), correlation (0.547401)*/
}; // compute the descriptor
void ComputeORB(const cv::Mat &img, vector<cv::KeyPoint> &keypoints, vector<DescType> &descriptors) {
const int half_patch_size = ;
const int half_boundary = ;
int bad_points = ;
for (auto &kp: keypoints) {
if (kp.pt.x < half_boundary || kp.pt.y < half_boundary ||
kp.pt.x >= img.cols - half_boundary || kp.pt.y >= img.rows - half_boundary) {
// outside
bad_points++;
descriptors.push_back({});
continue;
} float m01 = , m10 = ;
for (int dx = -half_patch_size; dx < half_patch_size; ++dx) {
for (int dy = -half_patch_size; dy < half_patch_size; ++dy) {
uchar pixel = img.at<uchar>(kp.pt.y + dy, kp.pt.x + dx);
m01 += dx * pixel;
m10 += dy * pixel;
}
} // angle should be arc tan(m01/m10);
float m_sqrt = sqrt(m01 * m01 + m10 * m10) + 1e-; // avoid divide by zero
float sin_theta = m01 / m_sqrt;
float cos_theta = m10 / m_sqrt; // compute the angle of this point
DescType desc(, );
for (int i = ; i < ; i++) {
uint32_t d = ;
for (int k = ; k < ; k++) {
int idx_pq = i * + k;
cv::Point2f p(ORB_pattern[idx_pq * ], ORB_pattern[idx_pq * + ]);
cv::Point2f q(ORB_pattern[idx_pq * + ], ORB_pattern[idx_pq * + ]); // rotate with theta
cv::Point2f pp = cv::Point2f(cos_theta * p.x - sin_theta * p.y, sin_theta * p.x + cos_theta * p.y)
+ kp.pt;
cv::Point2f qq = cv::Point2f(cos_theta * q.x - sin_theta * q.y, sin_theta * q.x + cos_theta * q.y)
+ kp.pt;
if (img.at<uchar>(pp.y, pp.x) < img.at<uchar>(qq.y, qq.x)) {
d |= << k;
}
}
desc[i] = d;
}
descriptors.push_back(desc);
} cout << "bad/total: " << bad_points << "/" << keypoints.size() << endl;
} // brute-force matching
void BfMatch(const vector<DescType> &desc1, const vector<DescType> &desc2, vector<cv::DMatch> &matches) {
const int d_max = ; for (size_t i1 = ; i1 < desc1.size(); ++i1) {
if (desc1[i1].empty()) continue;
cv::DMatch m{static_cast<int>(i1), , };
for (size_t i2 = ; i2 < desc2.size(); ++i2) {
if (desc2[i2].empty()) continue;
int distance = ;
for (int k = ; k < ; k++) {
distance += _mm_popcnt_u32(desc1[i1][k] ^ desc2[i2][k]);
}
if (distance < d_max && distance < m.distance) {
m.distance = distance;
m.trainIdx = i2;
}
}
if (m.distance < d_max) {
matches.push_back(m);
}
}
}
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