diff options
Diffstat (limited to 'intern/libmv/libmv/tracking/trklt_region_tracker.cc')
| -rw-r--r-- | intern/libmv/libmv/tracking/trklt_region_tracker.cc | 63 |
1 files changed, 34 insertions, 29 deletions
diff --git a/intern/libmv/libmv/tracking/trklt_region_tracker.cc b/intern/libmv/libmv/tracking/trklt_region_tracker.cc index 05ef3d1d272..7ffa7555467 100644 --- a/intern/libmv/libmv/tracking/trklt_region_tracker.cc +++ b/intern/libmv/libmv/tracking/trklt_region_tracker.cc @@ -20,27 +20,29 @@ #include "libmv/tracking/trklt_region_tracker.h" -#include "libmv/logging/logging.h" -#include "libmv/numeric/numeric.h" -#include "libmv/image/image.h" #include "libmv/image/convolve.h" +#include "libmv/image/image.h" #include "libmv/image/sample.h" +#include "libmv/logging/logging.h" +#include "libmv/numeric/numeric.h" namespace libmv { // TODO(keir): Switch this to use the smarter LM loop like in ESM. // Computes U and e from the Ud = e equation (number 14) from the paper. -static void ComputeTrackingEquation(const Array3Df &image_and_gradient1, - const Array3Df &image_and_gradient2, - double x1, double y1, - double x2, double y2, +static void ComputeTrackingEquation(const Array3Df& image_and_gradient1, + const Array3Df& image_and_gradient2, + double x1, + double y1, + double x2, + double y2, int half_width, double lambda, - Mat2f *U, - Vec2f *e) { + Mat2f* U, + Vec2f* e) { Mat2f A, B, C, D; - A = B = C = D = Mat2f::Zero(); + A = B = C = D = Mat2f::Zero(); Vec2f R, S, V, W; R = S = V = W = Vec2f::Zero(); @@ -57,9 +59,9 @@ static void ComputeTrackingEquation(const Array3Df &image_and_gradient1, Vec2f gI, gJ; gI << SampleLinear(image_and_gradient1, yy1, xx1, 1), - SampleLinear(image_and_gradient1, yy1, xx1, 2); + SampleLinear(image_and_gradient1, yy1, xx1, 2); gJ << SampleLinear(image_and_gradient2, yy2, xx2, 1), - SampleLinear(image_and_gradient2, yy2, xx2, 2); + SampleLinear(image_and_gradient2, yy2, xx2, 2); // Equation 15 from the paper. A += gI * gI.transpose(); @@ -77,26 +79,25 @@ static void ComputeTrackingEquation(const Array3Df &image_and_gradient1, Mat2f Di = B.transpose().inverse(); // Equation 14 from the paper. - *U = A*Di*C + lambda*Di*C - 0.5*B; - *e = (A + lambda*Mat2f::Identity())*Di*(V - W) + 0.5*(S - R); + *U = A * Di * C + lambda * Di * C - 0.5 * B; + *e = (A + lambda * Mat2f::Identity()) * Di * (V - W) + 0.5 * (S - R); } -static bool RegionIsInBounds(const FloatImage &image1, - double x, double y, - int half_window_size) { +static bool RegionIsInBounds(const FloatImage& image1, + double x, + double y, + int half_window_size) { // Check the minimum coordinates. int min_x = floor(x) - half_window_size - 1; int min_y = floor(y) - half_window_size - 1; - if (min_x < 0.0 || - min_y < 0.0) { + if (min_x < 0.0 || min_y < 0.0) { return false; } // Check the maximum coordinates. int max_x = ceil(x) + half_window_size + 1; int max_y = ceil(y) + half_window_size + 1; - if (max_x > image1.cols() || - max_y > image1.rows()) { + if (max_x > image1.cols() || max_y > image1.rows()) { return false; } @@ -104,10 +105,12 @@ static bool RegionIsInBounds(const FloatImage &image1, return true; } -bool TrkltRegionTracker::Track(const FloatImage &image1, - const FloatImage &image2, - double x1, double y1, - double *x2, double *y2) const { +bool TrkltRegionTracker::Track(const FloatImage& image1, + const FloatImage& image2, + double x1, + double y1, + double* x2, + double* y2) const { if (!RegionIsInBounds(image1, x1, y1, half_window_size)) { LG << "Fell out of image1's window with x1=" << x1 << ", y1=" << y1 << ", hw=" << half_window_size << "."; @@ -134,11 +137,14 @@ bool TrkltRegionTracker::Track(const FloatImage &image1, Vec2f e; ComputeTrackingEquation(image_and_gradient1, image_and_gradient2, - x1, y1, - *x2, *y2, + x1, + y1, + *x2, + *y2, half_window_size, lambda, - &U, &e); + &U, + &e); // Solve the linear system for the best update to x2 and y2. d = U.lu().solve(e); @@ -161,7 +167,6 @@ bool TrkltRegionTracker::Track(const FloatImage &image1, LG << "x=" << *x2 << ", y=" << *y2 << ", dx=" << d[0] << ", dy=" << d[1] << ", det=" << determinant; - // If the update is small, then we probably found the target. if (d.squaredNorm() < min_update_squared_distance) { LG << "Successful track in " << i << " iterations."; |