CVIVApr 10, 2024

Binomial Self-compensation for Motion Error in Dynamic 3D Scanning

arXiv:2404.06693v35 citationsh-index: 4ECCV
Originality Incremental advance
AI Analysis

This addresses motion error in dynamic 3D scanning for applications requiring high precision, representing an incremental improvement over existing methods.

The paper tackles motion-induced errors in dynamic 3D scanning using phase shifting profilometry by proposing a binomial self-compensation algorithm, which reduces ripple-like errors and achieves a depth map frame rate of 90 fps for high-accuracy reconstruction.

Phase shifting profilometry (PSP) is favored in high-precision 3D scanning due to its high accuracy, robustness, and pixel-wise property. However, a fundamental assumption of PSP that the object should remain static is violated in dynamic measurement, making PSP susceptible to object moving, resulting in ripple-like errors in the point clouds. We propose a pixel-wise and frame-wise loopable binomial self-compensation (BSC) algorithm to effectively and flexibly eliminate motion error in the four-step PSP. Our mathematical model demonstrates that by summing successive motion-affected phase frames weighted by binomial coefficients, motion error exponentially diminishes as the binomial order increases, accomplishing automatic error compensation through the motion-affected phase sequence, without the assistance of any intermediate variable. Extensive experiments show that our BSC outperforms the existing methods in reducing motion error, while achieving a depth map frame rate equal to the camera's acquisition rate (90 fps), enabling high-accuracy 3D reconstruction with a quasi-single-shot frame rate.

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