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@ -239,7 +239,8 @@ N.B.: Markers are not needed in Pose2Sim and were used here for validation
</details> </details>
## Camera calibration ## Camera calibration
> _**Convert a preexisting calibration file, or calculate intrinsic and extrinsic parameters from scratch.**_ \ > _**Calculate camera intrinsic properties and extrinsic locations and positions.\
> Convert a preexisting calibration file, or calculate intrinsic and extrinsic parameters from scratch.**_ \
> _**N.B.:**_ You can visualize camera calibration in 3D with my (experimental) [Maya-Mocap tool](https://github.com/davidpagnon/Maya-Mocap). > _**N.B.:**_ You can visualize camera calibration in 3D with my (experimental) [Maya-Mocap tool](https://github.com/davidpagnon/Maya-Mocap).
Open an Anaconda prompt or a terminal, type `ipython`.\ Open an Anaconda prompt or a terminal, type `ipython`.\
@ -255,6 +256,8 @@ Output:\
<img src="Content/CalibFile.png" width="760"> <img src="Content/CalibFile.png" width="760">
### Convert from Qualisys, Optitrack, Vicon, OpenCap, EasyMocap, or bioCV ### Convert from Qualisys, Optitrack, Vicon, OpenCap, EasyMocap, or bioCV
> N.B.: Since Pose2Sim uses the [Aniposelib](https://anipose.readthedocs.io/en/latest/aniposelibtutorial.html) format, calibration does not need to be run if you already have an [AniPose](https://github.com/lambdaloop/anipose) or [FreeMocap](https://github.com/freemocap/freemocap) calibration .toml file.
If you already have a calibration file, set `calibration_type` type to `convert` in your [User\Config.toml](https://github.com/perfanalytics/pose2sim/blob/main/Pose2Sim/Empty_project/User/Config.toml) file. If you already have a calibration file, set `calibration_type` type to `convert` in your [User\Config.toml](https://github.com/perfanalytics/pose2sim/blob/main/Pose2Sim/Empty_project/User/Config.toml) file.
- **From [Qualisys](https://www.qualisys.com):** - **From [Qualisys](https://www.qualisys.com):**
@ -857,6 +860,7 @@ If you want to contribute to Pose2Sim, please follow [this guide](https://docs.g
&#10004; **Calibration:** Easier and clearer calibration procedure: separate intrinsic and extrinsic parameter calculation, edit corner detection if some are wrongly detected (or not visible). &#10004; **Calibration:** Easier and clearer calibration procedure: separate intrinsic and extrinsic parameter calculation, edit corner detection if some are wrongly detected (or not visible).
&#10004; **Calibration:** Possibility to evaluate extrinsic parameters from cues on scene. &#10004; **Calibration:** Possibility to evaluate extrinsic parameters from cues on scene.
&#9634; **Calibration:** Once object points have been detected or clicked once, track them for live calibration of moving cameras. Propose to click again when they are lost. &#9634; **Calibration:** Once object points have been detected or clicked once, track them for live calibration of moving cameras. Propose to click again when they are lost.
&#9634; **Calibration:** More accurate extrinsic calibration with [aniposelib](https://anipose.readthedocs.io/en/latest/aniposelib-tutorial.html)
&#9634; **Calibration:** Fine-tune calibration with bundle adjustment. &#9634; **Calibration:** Fine-tune calibration with bundle adjustment.
&#9634; **Calibration:** Support ChArUco board detection (see [there](https://mecaruco2.readthedocs.io/en/latest/notebooks_rst/Aruco/sandbox/ludovic/aruco_calibration_rotation.html)). &#9634; **Calibration:** Support ChArUco board detection (see [there](https://mecaruco2.readthedocs.io/en/latest/notebooks_rst/Aruco/sandbox/ludovic/aruco_calibration_rotation.html)).
&#9634; **Calibration:** Calculate calibration with points rather than board. (1) SBA calibration with wand (cf [Argus](https://argus.web.unc.edu), see converter [here](https://github.com/backyardbiomech/DLCconverterDLT/blob/master/DLTcameraPosition.py)). Set world reference frame in the end. &#9634; **Calibration:** Calculate calibration with points rather than board. (1) SBA calibration with wand (cf [Argus](https://argus.web.unc.edu), see converter [here](https://github.com/backyardbiomech/DLCconverterDLT/blob/master/DLTcameraPosition.py)). Set world reference frame in the end.
@ -875,6 +879,7 @@ If you want to contribute to Pose2Sim, please follow [this guide](https://docs.g
&#10004; **Triangulation:** Show which frames had to be interpolated for each keypoint. &#10004; **Triangulation:** Show which frames had to be interpolated for each keypoint.
&#9634; **Triangulation:** [Undistort](https://docs.opencv.org/3.4/da/d54/group__imgproc__transform.html#ga887960ea1bde84784e7f1710a922b93c) 2D points before triangulating (and [distort](https://github.com/lambdaloop/aniposelib/blob/d03b485c4e178d7cff076e9fe1ac36837db49158/aniposelib/cameras.py#L301) them before computing reprojection error). &#9634; **Triangulation:** [Undistort](https://docs.opencv.org/3.4/da/d54/group__imgproc__transform.html#ga887960ea1bde84784e7f1710a922b93c) 2D points before triangulating (and [distort](https://github.com/lambdaloop/aniposelib/blob/d03b485c4e178d7cff076e9fe1ac36837db49158/aniposelib/cameras.py#L301) them before computing reprojection error).
&#9634; **Triangulation:** Multiple person kinematics (output multiple .trc coordinates files). Triangulate all persons with reprojection error above threshold, and identify them by minimizing their displacement across frames. &#9634; **Triangulation:** Multiple person kinematics (output multiple .trc coordinates files). Triangulate all persons with reprojection error above threshold, and identify them by minimizing their displacement across frames.
&#9634; **Triangulation:** Pre-compile `weighted_traingulation` and `reprojection` with `@jit(nopython=True, parallel=True)` for faster execution.
&#9634; **Triangulation:** Offer the possibility of triangulating with Sparse Bundle Adjustment (SBA), Extended Kalman Filter (EKF), Full Trajectory Estimation (FTE) (see [AcinoSet](https://github.com/African-Robotics-Unit/AcinoSet)). &#9634; **Triangulation:** Offer the possibility of triangulating with Sparse Bundle Adjustment (SBA), Extended Kalman Filter (EKF), Full Trajectory Estimation (FTE) (see [AcinoSet](https://github.com/African-Robotics-Unit/AcinoSet)).
&#9634; **Triangulation:** Solve limb swapping (although not really an issue with Body_25b). Try triangulating with opposite side if reprojection error too large. Alternatively, ignore right and left sides, use RANSAC or SDS triangulation, and then choose right or left by majority voting. More confidence can be given to cameras whose plane is the most coplanar to the right/left line. &#9634; **Triangulation:** Solve limb swapping (although not really an issue with Body_25b). Try triangulating with opposite side if reprojection error too large. Alternatively, ignore right and left sides, use RANSAC or SDS triangulation, and then choose right or left by majority voting. More confidence can be given to cameras whose plane is the most coplanar to the right/left line.
&#9634; **Triangulation:** Implement normalized DLT and RANSAC triangulation, Outlier rejection (sliding z-score?), as well as a [triangulation refinement step](https://doi.org/10.1109/TMM.2022.3171102). &#9634; **Triangulation:** Implement normalized DLT and RANSAC triangulation, Outlier rejection (sliding z-score?), as well as a [triangulation refinement step](https://doi.org/10.1109/TMM.2022.3171102).