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Documentation Index

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Overview

GeometricCamera is the abstract base class that defines the common interface for all camera models in ORB-SLAM3. It provides virtual methods for projection, unprojection, and two-view reconstruction that must be implemented by derived camera models. Header: CameraModels/GeometricCamera.h Namespace: ORB_SLAM3

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Camera Types

The class defines two camera type constants: 
const static unsigned int CAM_PINHOLE = 0;
const static unsigned int CAM_FISHEYE = 1;

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Constructors

GeometricCamera()
Default constructor. 
GeometricCamera(const std::vector<float> &_vParameters)
Constructs a camera with given parameter vector. Parameters:
  • _vParameters - Vector of camera parameters (format depends on derived class)

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Core Methods

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Projection

Project 3D points to 2D image coordinates. 
virtual cv::Point2f project(const cv::Point3f &p3D) = 0

virtual Eigen::Vector2d project(const Eigen::Vector3d &v3D) = 0

virtual Eigen::Vector2f project(const Eigen::Vector3f &v3D) = 0

virtual Eigen::Vector2f projectMat(const cv::Point3f &p3D) = 0
Parameters:
  • p3D / v3D - 3D point in camera coordinates
Returns: 2D point in image coordinates (pixels)

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Unprojection

Unproject 2D image points to 3D rays. 
virtual cv::Point3f unproject(const cv::Point2f &p2D) = 0

virtual Eigen::Vector3f unprojectEig(const cv::Point2f &p2D) = 0
Parameters:
  • p2D - 2D point in image coordinates (pixels)
Returns: 3D unit vector representing the ray direction

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Jacobian

virtual Eigen::Matrix<double,2,3> projectJac(const Eigen::Vector3d &v3D) = 0
Compute the Jacobian of the projection function. Parameters:
  • v3D - 3D point in camera coordinates
Returns: 2x3 Jacobian matrix ∂π/∂X

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Uncertainty

virtual float uncertainty2(const Eigen::Matrix<double,2,1> &p2D) = 0
Compute the squared uncertainty of a 2D point. Parameters:
  • p2D - 2D point in image coordinates
Returns: Uncertainty value

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Calibration Matrix

virtual cv::Mat toK() = 0

virtual Eigen::Matrix3f toK_() = 0
Return the camera calibration matrix K. Returns: 3x3 intrinsic calibration matrix

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Two-View Reconstruction

virtual 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
) = 0
Reconstruct 3D points and relative pose from two views. Parameters:
  • vKeys1 - Keypoints from first image
  • vKeys2 - Keypoints from second image
  • vMatches12 - Matches between views
  • T21 - Output: relative pose from view 1 to view 2
  • vP3D - Output: triangulated 3D points
  • vbTriangulated - Output: flags indicating successful triangulation
Returns: true if reconstruction successful

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Epipolar Constraint

virtual bool epipolarConstrain(
    GeometricCamera *otherCamera,
    const cv::KeyPoint &kp1,
    const cv::KeyPoint &kp2,
    const Eigen::Matrix3f &R12,
    const Eigen::Vector3f &t12,
    const float sigmaLevel,
    const float unc
) = 0
Check if two keypoints satisfy the epipolar constraint. Parameters:
  • otherCamera - Camera model for second view
  • kp1 - Keypoint in first image
  • kp2 - Keypoint in second image
  • R12 - Rotation from camera 1 to camera 2
  • t12 - Translation from camera 1 to camera 2
  • sigmaLevel - Sigma level for uncertainty
  • unc - Uncertainty threshold
Returns: true if constraint satisfied

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Match and Triangulate

virtual bool matchAndtriangulate(
    const cv::KeyPoint &kp1,
    const cv::KeyPoint &kp2,
    GeometricCamera *pOther,
    Sophus::SE3f &Tcw1,
    Sophus::SE3f &Tcw2,
    const float sigmaLevel1,
    const float sigmaLevel2,
    Eigen::Vector3f &x3Dtriangulated
) = 0
Match two keypoints and triangulate their 3D position. Parameters:
  • kp1 - Keypoint in first image
  • kp2 - Keypoint in second image
  • pOther - Camera model for second view
  • Tcw1 - Pose of first camera
  • Tcw2 - Pose of second camera
  • sigmaLevel1 - Sigma level for first keypoint
  • sigmaLevel2 - Sigma level for second keypoint
  • x3Dtriangulated - Output: triangulated 3D point
Returns: true if triangulation successful

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Parameter Access

float getParameter(const int i)
Get parameter at index i. 
void setParameter(const float p, const size_t i)
Set parameter at index i to value p. 
size_t size()
Get number of parameters.

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Identification

unsigned int GetId()
Get unique camera ID. 
unsigned int GetType()
Get camera type (CAM_PINHOLE or CAM_FISHEYE).

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Derived Classes

ORB-SLAM3 provides two implementations:
  • Pinhole - Standard pinhole camera model with radial-tangential distortion
  • KannalaBrandt8 - Fisheye camera model for wide-angle lenses

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See Also

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