Created
June 18, 2013 14:47
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Extract a single SIFT feature vector (global SIFT) from an entire image.
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| void extractGSIFT(const cv::Mat& src, std::vector<float>& feature) | |
| { | |
| const int W = 200; | |
| const int H = 200; | |
| const int NBP = 4; | |
| const int NBO = 8; | |
| const bool USEW = true; | |
| cv::Mat gray; | |
| cv::Mat img; | |
| cv::cvtColor(src, gray, CV_RGB2GRAY); | |
| cv::resize(gray, img, cv::Size(W, H)); | |
| cv::blur(img, img, cv::Size(5, 5)); | |
| feature.resize(NBP * NBP * NBO, 0.0f); | |
| for (int y = 1; y < H - 1; ++y) { | |
| for (int x = 1; x < W - 1; ++x) { | |
| const float dx = 0.5f * (img.at<uchar>(y, x + 1) - img.at<uchar>(y, x - 1)); | |
| const float dy = 0.5f * (img.at<uchar>(y + 1, x) - img.at<uchar>(y - 1, x)); | |
| const float m = std::sqrt(dx * dx + dy * dy); | |
| const float o = std::fmod(std::atan2(dy, dx) + 2 * (float)M_PI, 2 * (float)M_PI); | |
| const float nx = (float)x * NBP / W; | |
| const float ny = (float)y * NBP / H; | |
| const float nt = o * NBO / (2 * (float)M_PI); | |
| const int binx = (int)std::floor(nx - 0.5f); | |
| const int biny = (int)std::floor(ny - 0.5f); | |
| const int bint = (int)std::floor(nt); | |
| const float rbinx = nx - (binx + 0.5f); | |
| const float rbiny = ny - (biny + 0.5f); | |
| const float rbint = nt - bint; | |
| const float wsigma = 0.5f * NBP; | |
| float win = 1.0f; | |
| if (USEW) { | |
| float a = (nx - 0.5f * NBP) * (nx - 0.5f * NBP) + (ny - 0.5f * NBP) * (ny - 0.5f * NBP); | |
| win = std::exp(- a / (2.0f * wsigma * wsigma)); | |
| } | |
| for (int dbinx = 0; dbinx < 2; ++dbinx) { | |
| for (int dbiny = 0; dbiny < 2; ++dbiny) { | |
| for (int dbint = 0; dbint < 2; ++dbint) { | |
| if (binx + dbinx >= 0 && | |
| binx + dbinx < NBP && | |
| biny + dbiny >= 0 && | |
| biny + dbiny < NBP) | |
| { | |
| const float weight = win * m * std::abs(1.0f - dbinx - rbinx) * std::abs(1.0f - dbiny - rbiny) * std::abs(1.0f - dbint - rbint); | |
| feature[(biny + dbiny) * NBP * NBO + (binx + dbinx) * NBO + ((bint + dbint) % NBO)] += weight; | |
| } | |
| } | |
| } | |
| } | |
| } | |
| } | |
| const float sum = std::accumulate(feature.begin(), feature.end(), 0.0f); | |
| for (int i = 0; i < feature.size(); ++i) { | |
| feature[i] = std::sqrt(feature[i] / sum); | |
| } | |
| } |
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