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Overview
Pinhole implements the standard pinhole camera model with perspective projection. It extends GeometricCamera and is used for conventional cameras with narrow to moderate field-of-view.
Header: CameraModels/Pinhole.h
Namespace: ORB_SLAM3
Base Class: GeometricCamera
Camera Parameters
The pinhole model uses 4 intrinsic parameters:
fx - Focal length in x direction (pixels)fy - Focal length in y direction (pixels)cx - Principal point x coordinate (pixels)cy - Principal point y coordinate (pixels)
Note: Distortion coefficients are stored separately in the Settings class.
Constructors
Default constructor with 4 parameters.
Pinhole(const std::vector<float> _vParameters)
_vParameters - Vector [fx, fy, cx, cy]
Pinhole(Pinhole *pPinhole)
pPinhole - Source pinhole camera
Projection Methods
Project 3D points to 2D image coordinates using perspective projection.
cv::Point2f project(const cv::Point3f &p3D)
Eigen::Vector2d project(const Eigen::Vector3d &v3D)
Eigen::Vector2f project(const Eigen::Vector3f &v3D)
Eigen::Vector2f projectMat(const cv::Point3f &p3D)
p3D / v3D - 3D point in camera coordinates
Returns: 2D point in image coordinates (pixels)
Projection equation:
u = fx * X/Z + cx
v = fy * Y/Z + cy
Unprojection Methods
Unproject 2D image points to 3D unit rays.
cv::Point3f unproject(const cv::Point2f &p2D)
Eigen::Vector3f unprojectEig(const cv::Point2f &p2D)
p2D - 2D point in image coordinates (pixels)
Returns: 3D unit vector representing the ray direction
Unprojection equation:
X = (u - cx) / fx
Y = (v - cy) / fy
Z = 1
result = [X, Y, Z] / norm([X, Y, Z])
Jacobian
Eigen::Matrix<double,2,3> projectJac(const Eigen::Vector3d &v3D)
v3D - 3D point in camera coordinates
Returns: 2x3 Jacobian matrix ∂π/∂X
Jacobian form:
∂π/∂X = [fx/Z 0 -fx*X/Z²]
[ 0 fy/Z -fy*Y/Z²]
Uncertainty
float uncertainty2(const Eigen::Matrix<double,2,1> &p2D)
p2D - 2D point in image coordinates
Returns: Uncertainty value
Calibration Matrix
Return the intrinsic calibration matrix K.
Returns: 3x3 matrix:
[fx 0 cx]
[ 0 fy cy]
[ 0 0 1]
Two-View Reconstruction
bool ReconstructWithTwoViews(
const std::vector<cv::KeyPoint> &vKeys1,
const std::vector<cv::KeyPoint> &vKeys2,
const std::vector<int> &vMatches12,
Sophus::SE3f &T21,
std::vector<cv::Point3f> &vP3D,
std::vector<bool> &vbTriangulated
)
vKeys1 - Keypoints from first imagevKeys2 - Keypoints from second imagevMatches12 - Correspondences between viewsT21 - Output: relative transformation from view 1 to view 2vP3D - Output: triangulated 3D pointsvbTriangulated - Output: success flags for each point
Returns: true if reconstruction successful
Process:
- Compute fundamental matrix from matches
- Recover essential matrix using K
- Decompose essential matrix to get R and t
- Triangulate points and check cheirality
Epipolar Constraint
bool epipolarConstrain(
GeometricCamera *pCamera2,
const cv::KeyPoint &kp1,
const cv::KeyPoint &kp2,
const Eigen::Matrix3f &R12,
const Eigen::Vector3f &t12,
const float sigmaLevel,
const float unc
)
pCamera2 - Second camera modelkp1 - Keypoint in first imagekp2 - Keypoint in second imageR12 - Rotation from camera 1 to 2t12 - Translation from camera 1 to 2sigmaLevel - Uncertainty scale factorunc - Uncertainty threshold
Returns: true if epipolar constraint satisfied
Constraint: x2ᵀ * E * x1 = 0 where E = [t]×R
Comparison
bool IsEqual(GeometricCamera *pCam)
pCam - Camera to compare against
Returns: true if parameters match
Stream Operators
friend std::ostream& operator<<(std::ostream &os, const Pinhole &ph)
friend std::istream& operator>>(std::istream &is, Pinhole &ph)
Usage Example
// Create pinhole camera
std::vector<float> params = {fx, fy, cx, cy};
Pinhole* pCamera = new Pinhole(params);
// Project 3D point
cv::Point3f point3D(1.0f, 0.5f, 2.0f);
cv::Point2f point2D = pCamera->project(point3D);
// Unproject to ray
cv::Point3f ray = pCamera->unproject(point2D);
// Get calibration matrix
Eigen::Matrix3f K = pCamera->toK_();
Camera Type
Pinhole cameras have type CAM_PINHOLE (value 0).
See Also
