homography.h

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/* Copyright (C) 2013-2016, The Regents of The University of Michigan.
All rights reserved.
This software was developed in the APRIL Robotics Lab under the
direction of Edwin Olson, ebolson@umich.edu. This software may be
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#pragma once
 
#include "matd.h"
#include "zarray.h"
 
#ifdef __cplusplus
extern "C" {
#endif
 
    /** Given a 3x3 homography matrix and the focal lengths of the
     * camera, compute the pose of the tag. The focal lengths should
     * be given in pixels. For example, if the camera's focal length
     * is twice the width of the sensor, and the sensor is 600 pixels
     * across, the focal length in pixels is 2*600. Note that the
     * focal lengths in the fx and fy direction will be approximately
     * equal for most lenses, and is not a function of aspect ratio.
     *
     * Theory: The homography matrix is the product of the camera
     * projection matrix and the tag's pose matrix (the matrix that
     * projects points from the tag's local coordinate system to the
     * camera's coordinate frame).
     *
    * [ h00 h01 h02 h03] = [ fx   0     cx 0 ] [ R00 R01 R02 TX ]
     * [ h10 h11 h12 h13] = [ 0    fy    cy 0 ] [ R10 R11 R12 TY ]
     * [ h20 h21 h22 h23] = [ 0    0      s 0 ] [ R20 R21 R22 TZ ]
     *                                          [ 0   0   0   1  ]
     *
     * fx is the focal length in the x direction of the camera
     * (typically measured in pixels), fy is the focal length. cx and
     * cy give the focal center (usually the middle of the image), and
     * s is either +1 or -1, depending on the conventions you use. (We
     * use 1.)
 
     * When observing a tag, the points we project in world space all
     * have z=0, so we can form a 3x3 matrix by eliminating the 3rd
     * column of the pose matrix.
     *
     * [ h00 h01 h02 ] = [ fx   0    cx 0 ] [ R00 R01 TX ]
     * [ h10 h11 h12 ] = [ 0    fy   cy 0 ] [ R10 R11 TY ]
     * [ h20 h21 h22 ] = [ 0    0     s 0 ] [ R20 R21 TZ ]
     *                                      [ 0   0   1  ]
     *
     * (note that these h's are different from the ones above.)
     *
     * We can multiply the right-hand side to yield a set of equations
     * relating the values of h to the values of the pose matrix.
     *
     * There are two wrinkles. The first is that the homography matrix
     * is known only up to scale. We recover the unknown scale by
     * constraining the magnitude of the first two columns of the pose
     * matrix to be 1. We use the geometric average scale. The sign of
     * the scale factor is recovered by constraining the observed tag
     * to be in front of the camera. Once scaled, we recover the first
     * two colmuns of the rotation matrix. The third column is the
     * cross product of these.
     *
     * The second wrinkle is that the computed rotation matrix might
     * not be exactly orthogonal, so we perform a polar decomposition
     * to find a good pure rotation approximation.
     *
     * Tagsize is the size of the tag in your desired units. I.e., if
     * your tag measures 0.25m along the side, your tag size is
     * 0.25. (The homography is computed in terms of *half* the tag
     * size, i.e., that a tag is 2 units wide as it spans from -1 to
     * +1, but this code makes the appropriate adjustment.)
     *
     * A note on signs:
     *
     * The code below incorporates no additional negative signs, but
     * respects the sign of any parameters that you pass in. Flipping
     * the signs allows you to modify the projection to suit a wide
     * variety of conditions.
     *
     * In the "pure geometry" projection matrix, the image appears
     * upside down; i.e., the x and y coordinates on the left hand
     * side are the opposite of those on the right of the camera
     * projection matrix. This would happen for all parameters
     * positive: recall that points in front of the camera have
     * negative Z values, which will cause the sign of all points to
     * flip.
     *
     * However, most cameras flip things so that the image appears
     * "right side up" as though you were looking through the lens
     * directly. This means that the projected points should have the
     * same sign as the points on the right of the camera projection
     * matrix. To achieve this, flip fx and fy.
     *
     * One further complication: cameras typically put y=0 at the top
     * of the image, instead of the bottom. Thus you generally want to
     * flip y yet again (so it's now positive again).
     *
     * General advice: you probably want fx negative, fy positive, cx
     * and cy positive, and s=1.
     **/
 
// correspondences is a list of float[4]s, consisting of the points x
// and y concatenated. We will compute a homography such that y = Hx
// Specifically, float [] { a, b, c, d } where x = [a b], y = [c d].
 
 
#define HOMOGRAPHY_COMPUTE_FLAG_INVERSE 1
#define HOMOGRAPHY_COMPUTE_FLAG_SVD 0
 
matd_t *homography_compute(zarray_t *correspondences, int flags);
 
//void homography_project(const matd_t *H, double x, double y, double *ox, double *oy);
static inline void homography_project(const matd_t *H, double x, double y, double *ox, double *oy)
{
    double xx = MATD_EL(H, 0, 0)*x + MATD_EL(H, 0, 1)*y + MATD_EL(H, 0, 2);
    double yy = MATD_EL(H, 1, 0)*x + MATD_EL(H, 1, 1)*y + MATD_EL(H, 1, 2);
    double zz = MATD_EL(H, 2, 0)*x + MATD_EL(H, 2, 1)*y + MATD_EL(H, 2, 2);
 
    *ox = xx / zz;
    *oy = yy / zz;
}
 
// assuming that the projection matrix is:
// [ fx 0  cx 0 ]
// [  0 fy cy 0 ]
// [  0  0  1 0 ]
//
// And that the homography is equal to the projection matrix times the model matrix,
// recover the model matrix (which is returned). Note that the third column of the model
// matrix is missing in the expression below, reflecting the fact that the homography assumes
// all points are at z=0 (i.e., planar) and that the element of z is thus omitted.
// (3x1 instead of 4x1).
//
// [ fx 0  cx 0 ] [ R00  R01  TX ]    [ H00 H01 H02 ]
// [  0 fy cy 0 ] [ R10  R11  TY ] =  [ H10 H11 H12 ]
// [  0  0  1 0 ] [ R20  R21  TZ ] =  [ H20 H21 H22 ]
//                [  0    0    1 ]
//
// fx*R00 + cx*R20 = H00   (note, H only known up to scale; some additional adjustments required; see code.)
// fx*R01 + cx*R21 = H01
// fx*TX  + cx*TZ  = H02
// fy*R10 + cy*R20 = H10
// fy*R11 + cy*R21 = H11
// fy*TY  + cy*TZ  = H12
// R20 = H20
// R21 = H21
// TZ  = H22
matd_t *homography_to_pose(const matd_t *H, double fx, double fy, double cx, double cy);
 
// Similar to above
// Recover the model view matrix assuming that the projection matrix is:
//
// [ F  0  A  0 ]     (see glFrustrum)
// [ 0  G  B  0 ]
// [ 0  0  C  D ]
// [ 0  0 -1  0 ]
 
matd_t *homography_to_model_view(const matd_t *H, double F, double G, double A, double B);
 
#ifdef __cplusplus
}
#endif