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arXiv · 2305.17673

OSPC: Online Sequential Photometric Calibration

Jawad Haidar·Douaa Khalil·Daniel Asmar
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Abstract

Photometric calibration is essential to many computer vision applications. One of its key benefits is enhancing the performance of Visual SLAM, especially when it depends on a direct method for tracking, such as the standard KLT algorithm. Another advantage could be in retrieving the sensor irradiance values from measured intensities, as a pre-processing step for some vision algorithms, such as shape-from-shading. Current photometric calibration systems rely on a joint optimization problem and encounter an ambiguity in the estimates, which can only be resolved using ground truth information. We propose a novel method that solves for photometric parameters using a sequential estimation approach. Our proposed method achieves high accuracy in estimating all parameters; furthermore, the formulations are linear and convex, which makes the solution fast and suitable for online applications. Experiments on a Visual Odometry system validate the proposed method and demonstrate its advantages.

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Jawad Haidar, Douaa Khalil, Daniel Asmar. 2023-05-28. OSPC: Online Sequential Photometric Calibration. https://arxiv.org/abs/2305.17673

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