1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
|
/* ----------------------------------------------------------------------------
* GTSAM Copyright 2010, Georgia Tech Research Corporation,
* Atlanta, Georgia 30332-0415
* All Rights Reserved
* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
* See LICENSE for the license information
* -------------------------------------------------------------------------- */
/**
* @file CameraResectioning.cpp
* @brief An example of gtsam for solving the camera resectioning problem
* @author Duy-Nguyen Ta
* @date Aug 23, 2011
*/
#include <gtsam/inference/Symbol.h>
#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
#include <gtsam/geometry/PinholeCamera.h>
#include <gtsam/geometry/Cal3_S2.h>
#include <boost/make_shared.hpp>
using namespace gtsam;
using namespace gtsam::noiseModel;
using symbol_shorthand::X;
/**
* Unary factor on the unknown pose, resulting from meauring the projection of
* a known 3D point in the image
*/
class ResectioningFactor: public NoiseModelFactorN<Pose3> {
typedef NoiseModelFactorN<Pose3> Base;
Cal3_S2::shared_ptr K_; ///< camera's intrinsic parameters
Point3 P_; ///< 3D point on the calibration rig
Point2 p_; ///< 2D measurement of the 3D point
public:
/// Construct factor given known point P and its projection p
ResectioningFactor(const SharedNoiseModel& model, const Key& key,
const Cal3_S2::shared_ptr& calib, const Point2& p, const Point3& P) :
Base(model, key), K_(calib), P_(P), p_(p) {
}
/// evaluate the error
Vector evaluateError(const Pose3& pose, boost::optional<Matrix&> H =
boost::none) const override {
PinholeCamera<Cal3_S2> camera(pose, *K_);
return camera.project(P_, H, boost::none, boost::none) - p_;
}
};
/*******************************************************************************
* Camera: f = 1, Image: 100x100, center: 50, 50.0
* Pose (ground truth): (Xw, -Yw, -Zw, [0,0,2.0]')
* Known landmarks:
* 3D Points: (10,10,0) (-10,10,0) (-10,-10,0) (10,-10,0)
* Perfect measurements:
* 2D Point: (55,45) (45,45) (45,55) (55,55)
*******************************************************************************/
int main(int argc, char* argv[]) {
/* read camera intrinsic parameters */
Cal3_S2::shared_ptr calib(new Cal3_S2(1, 1, 0, 50, 50));
/* 1. create graph */
NonlinearFactorGraph graph;
/* 2. add factors to the graph */
// add measurement factors
SharedDiagonal measurementNoise = Diagonal::Sigmas(Vector2(0.5, 0.5));
boost::shared_ptr<ResectioningFactor> factor;
graph.emplace_shared<ResectioningFactor>(measurementNoise, X(1), calib,
Point2(55, 45), Point3(10, 10, 0));
graph.emplace_shared<ResectioningFactor>(measurementNoise, X(1), calib,
Point2(45, 45), Point3(-10, 10, 0));
graph.emplace_shared<ResectioningFactor>(measurementNoise, X(1), calib,
Point2(45, 55), Point3(-10, -10, 0));
graph.emplace_shared<ResectioningFactor>(measurementNoise, X(1), calib,
Point2(55, 55), Point3(10, -10, 0));
/* 3. Create an initial estimate for the camera pose */
Values initial;
initial.insert(X(1),
Pose3(Rot3(1, 0, 0, 0, -1, 0, 0, 0, -1), Point3(0, 0, 2)));
/* 4. Optimize the graph using Levenberg-Marquardt*/
Values result = LevenbergMarquardtOptimizer(graph, initial).optimize();
result.print("Final result:\n");
return 0;
}
|
