Wild + multiple sparse

• When use this: sparse cameras, hard to calibrate for colmap;
• Idea: Use an extra phone to record the scene.
• Here you can find the example data.

Capture

<sup>background

ground

scan</sup>

Place the data as follows:

<calib_data>
├── background1f
│   ├── images
│   └── scan.mp4
└── ground1f
    └── images

Calibration

1. Detect the chessboard

# detect the chessboard
python3 apps/calibration/detect_chessboard.py ${root}/ground1f --out ${root}/ground1f/output --pattern 9,6 --grid 0.1
# check the chessboard detection
python3 apps/annotation/annot_calib.py ${root}/ground1f --annot chessboard --mode chessboard

2. Calibrate by colmap

python3 apps/calibration/calib_static_dynamic_by_colmap.py ${root}/background1f ${root}/colmap --colmap ${colmap} --step 4
# check with colmap
${colmap} gui --database_path ${root}/colmap/database.db --image_path ${root}/colmap/images --import_path ${root}/colmap/sparse/0

3. Align to the chessboard

python3 apps/calibration/align_colmap_ground.py ${root}/colmap/sparse/0 ${root}/colmap/align --plane_by_chessboard ${root}/ground1f --prefix static/