xuhao1 / multicamerapose

Multi Camera Pose Estimation

Multi Camera Pose Estimation

Code for estimating the absolute pose of a multi-camera system from a set of 2D-3D matches.

Setup

This project has the following dependencies:

• RansacLib
• PoseLib
• Eigen3
• Ceres

RansacLib and PoseLib are included as a submodule. After cloning the repository, run

git submodule update --init --recursive

To compile the project (under Linux), simple type

mkdir build
cd build/
cmake -DCMAKE_BUILD_TYPE=Release ../
make

Running the executables

There are two executables" fixed_rig_camera_pose and multi_camera_pose. fixed_rig_camera_pose assumes that the absolute scale of the transformation between the images is known. multi_camera_pose does not require the scale to be known, e.g., when the poses are estimated by SLAM, but rather estimates the scale. Both executables define multi-camera rigs define from sequences of images and expect a list of 2D-3D matches to be given for each image in the multi-camera system. Both executables share the same command line parameters:

• images_with_intrinsics is the file name of a text file that contains image names, camera intrinsics, and camera extrinsics. Each line consists of the following information:
  • image_name: the name of the image.
  • intrinsics: the intrinsics of the image, consisting of a camera type and the parameters. We use Colmaps camera definition. Please see Colmap's camera definitions. An example for this part is SIMPLE_RADIAL 1024 1024 640.0 512 512 0.2.
  • The camera extrinsics in the form qw qx qy qz cx cy cz, where qw qx qy qz is a unit quaternion defining a rotation from world to camera coordinates for this image and cx cy cz is the position of the image in world coordinates. I.e., a point Xw in world coordinates is transformed into the local camera coordinate system of the image as Xc = R * (Xw - c), where R is the rotation matrix defined by the quaternion and c is the position of the image in the world coordinate system. These poses can be defined in an arbitrary coordinate frame. The executables will automatically extract relative poses between the images.
• outfile is the file name of a text file into which the estimated poses will be written. For each image in images_with_intrinsics, a pose will be written (if a corresponding pose can be estimated) in a line of the output file. The format of that line is image_name qw qx qy qz tx ty tz. Here image_name is the name of the image (as specified in images_with_intrinsics, qw qx qy qz again is a unit quaternion defining the rotation from the coordinate system of the 3D points (see below) to the local camera coordinate system and tx ty tz is the corresponding translation. If R is the rotation matrix corresponding to the quaternion, then a point Xw in world coordinates is transformed into the local camera coordinate system as Xc = R * Xw + t, where t is the translation vector given by tx ty tz.
• inlier_threshold: the inlier threshold to be used in RANSAC, given in pixels.
• num_lo_steps: the number of local optimization steps performed in RANSAC whenever a new best minimal pose is found.
• invert_Y_Z: the 2D-3D matches for each image are read from text files, where each line has the format x y X Y Z. Here, x y defines a 2D keypoint. Set this variable to 1 if x y is given in a coordinate system where the y-axis is pointing upwards.
• points_centered: set to 1 if the 2D keypoint coordinates x y are already centered around the principal point. If set to 0, the executables will center the keypoints before using them.
• undistortion_needed: set to 1 if the 2D keypoint coordinates need to be undistorted and to 0 if the keypoints that are read from the text files are already undistorted.
• sequence_length: both executables assume that the images specified in images_with_intrinsics are given in sequential order. If set to k, e.g., 3, fixed_rig_camera_pose will use the first k images to define a multi-camera system and attempt to localize them jointly. It will then use the next k images to define the next multi-camera rig, etc. multi_camera_pose will use the first k images to define the first multi-camera system. It will then use images 2, ..., k+1 to define the next multi-camera system, then3, ..., k + 2, etc.
• [match-file postfix] (optional): the postfix of the match files, set to .individual_datasets.matches.txt per default. For a given image name a.jpg in images_with_intrinsics, both executables will attempt to load 2D-3D matches from a text file called a.jpg.individual_datasets.matches.txt (for the default value). The text file stores each 2D-3D match in a single line, with the format x y X Y Z. Here, x y is the 2D coordinate of the matching 2D point and X Y Z is the corresponding 3D point.

Simply calling one of the programs without parameters will give you a list of command line arguments.

Citing

When using this software for publications, please cite

@inproceedings{wald2020,
  title={{Beyond Controlled Environments: 3D Camera Re-Localization in Changing Indoor Scenes}},
  author={Wald, Johanna and Sattler, Torsten and Golodetz, Stuart and Cavallari, Tommaso and Tombari, Federico},
  booktitle = {Proceedings IEEE European Conference on Computer Vision (ECCV)},
  year = {2020}
}

When using the pose estimators based on the GP3P or GP4Ps solvers, please cite

@InProceedings{Kukelova2016CVPR,
  author = {Kukelova, Zuzana and Heller, Jan and Fitzgibbon, Andrew},
  title = {Efficient Intersection of Three Quadrics and Applications in Computer Vision},
  booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016}
}