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Triangulation: Why Optimize?

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arxiv 1907.11917 v2 pith:V3IFRUDV submitted 2019-07-27 cs.CV

classification cs.CV
keywords errorsparallaxmethodsolutiontriangulationacceptedaccuracyachieving
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For decades, it has been widely accepted that the gold standard for two-view triangulation is to minimize the cost based on reprojection errors. In this work, we challenge this idea. We propose a novel alternative to the classic midpoint method that leads to significantly lower 2D errors and parallax errors. It provides a numerically stable closed-form solution based solely on a pair of backprojected rays. Since our solution is rotationally invariant, it can also be applied for fisheye and omnidirectional cameras. We show that for small parallax angles, our method outperforms the state-of-the-art in terms of combined 2D, 3D and parallax accuracy, while achieving comparable speed.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. CuSfM: CUDA-Accelerated Structure-from-Motion

    cs.CV 2025-10 conditional novelty 5.0 of 10

    A CUDA-accelerated SfM system reports faster offline mapping than COLMAP and better trajectory accuracy when initialized with odometry-like poses, though the comparison is not fully fair.

  2. 3D Trajectory Reconstruction of Moving Points Based on Asynchronous Cameras

    cs.CV 2025-05 conditional novelty 5.0 of 10

    Jointly estimates camera time offsets, per-frame rotations, and target motion parameters (temporal polynomials) in one bundle adjustment for asynchronous multi-camera 3D trajectory reconstruction.

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