Beyond Checkerboards: Advantages of Photogrammetric Camera Calibration for Robust 3D Vision and Novel-View Generation

Imagery is fundamental to modern scientific research, making robust intrinsic camera calibration indispensable for accurate visual inference. The checkerboard-based calibration method has long been favored for its simplicity and ease of deployment and is widely used even in mission-critical computer vision pipelines. However, its limitations in modeling high-precision camera geometry can compromise downstream performance in tasks requiring geometric accuracy. This work revisits camera calibration through the lens of photogrammetric self-calibration (PSC) and demonstrates that PSC consistently outperforms the checkerboard method in both accuracy and precision across a range of vision tasks, including 3D reconstruction with structure from motion (SfM), visual simultaneous localization and mapping (SLAM), and novel-view synthesis and reconstruction. The findings advocate for a shift toward calibration methods that better reflect the physical and projective properties of camera systems in real-world deployments for critical computer vision applications.

Recommended citation: Bharadwaj, A. & Lichti, D. D. (2026). "Beyond Checkerboards: Advantages of Photogrammetric Camera Calibration for Robust 3D Vision and Novel-View Generation." Remote Sensing. 18(13), 2220.
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