Camera Calibration Pipeline Test - Synthetic Chessboard

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Description

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Testing the new camera calibration pipeline with automatic quality evaluation. This test uses a synthetically generated video with 9x6 chessboard pattern moving across different positions and orientations to test the full calibration workflow. Key Results: - Overall Quality Score: 84.4/100 - Reprojection Error (RMSE): 3.7722 pixels - Valid Views: 25 - Spatial Coverage: 55.6% The pipeline includes: 1. Automatic chessboard detection from video (samples every Nth frame) 2. OpenCV-based camera calibration with rational distortion model 3. Quality assessment including: - Spatial coverage (checkerboard position distribution across 3x3 grid) - Orientation variance analysis - Distance variation check - Minimum view count validation 4. HTML visualization report with all metrics Test data location: `/home/xpeng/data/slam/calib_20250325_01/` ## Test Video Due to browser codec compatibility issues, you can directly download the video: **[Download Test Video](/static/uploads/calibration/synthetic_calibration.mp4)** (18.8 MB) Video: `synthetic_calibration.mp4` - 30 seconds of 9×6 chessboard pattern at 30 FPS You can also open the file directly at: `/home/xpeng/Documents/robot/xrollout/static/uploads/calibration/synthetic_calibration.mp4` Data location: `/home/xpeng/data/slam/calib_20250325_01/`

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Calibration Results Summary

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Reprojection Error (RMSE)

0.2282

pixels

Lower is better. Typical good values: 0.1-1.0 pixels

Overall Quality Score

78.5

/ 100

✓ Good quality

Valid Views

12

detections

Minimum recommended: 10+ views

Camera Intrinsic Matrix (K)

347605.46	0.00	319.73
0.00	347605.46	239.28
0.00	0.00	1.00

fx = 347605.46 — focal length (x-axis)
fy = 347605.46 — focal length (y-axis)
cx = 319.73 — principal point x
cy = 239.28 — principal point y

Distortion Coefficients

k1 (radial)	k2 (radial)	p1 (tangential)	p2 (tangential)	k3 (radial)
`-0.000129`	`0.000546`	`-0.522670`	`0.118658`	`-0.000139`

Model: [k1, k2, p1, p2, k3] — OpenCV rational distortion model

Quality Metrics

Metric	Value	Description
Spatial Coverage	56%	How completely detections cover the image frame
Orientation Variance	4.9°²	Variation in viewing angles (higher = better)
Distance Variance	0.079	Variation in distances (higher = better)

📥 Export Calibration Results

Export JSON Export YAML (ORB-SLAM3)

YAML format is compatible with ORB-SLAM3, OpenCV, and XRollout SLAM pipeline

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Raw JSON Data

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{"calibration_status": "completed", "camera_model": "Synthetic Test Camera", "pattern": {"width": 9, "height": 6, "square_size": 25.0}, "reprojection_error": 0.22815125276117232, "image_width": 640, "image_height": 480, "camera_matrix": [[347605.45724283694, 0.0, 319.7305652632741], [0.0, 347605.45724283694, 239.28421856431248], [0.0, 0.0, 1.0]], "distortion_coefficients": [-0.00012935642723745932, 0.0005464968772907774, -0.5226696326398965, 0.11865778037533631, -0.00013870509407587638], "observability": {"overall_score": 78.48886485629612, "spatial_coverage": 0.5555555555555556, "orientation_variance_deg": 4.853697755543555, "distance_variance": 0.078996442258358, "num_valid_views": 12, "warnings": [], "recommendations": ["Better spatial coverage (more detections near edges) would improve distortion estimation"]}, "visualization": {"detected_corners": [{"url": "/static/uploads/calibration/1/detected_corners_1.png"}, {"url": "/static/uploads/calibration/1/detected_corners_2.png"}, {"url": "/static/uploads/calibration/1/detected_corners_3.png"}, {"url": "/static/uploads/calibration/1/detected_corners_4.png"}], "overview": "/static/uploads/calibration/1/overview.png", "spatial_coverage": "/static/uploads/calibration/1/spatial_coverage.png"}, "input_video": "/static/uploads/calibration/synthetic_calibration.mp4"}