Robust Phase-Shifting Profilometry for Arbitrary Motion

TL;DR

This paper introduces a robust phase-shifting profilometry method capable of high-fidelity 3D reconstruction under complex arbitrary motions, including 6-DoF, non-rigid deformations, and multi-target movements, by effectively compensating motion-induced errors.

Contribution

The paper proposes a novel RPSP-AM technique that combines pixel-wise optical flow alignment and a binomial self-compensation method to eliminate motion artifacts in PSP.

Findings

Outperforms state-of-the-art methods in challenging motion scenarios.

Effectively eliminates ghosting artifacts and ripple distortions.

Enables accurate 3D reconstruction in complex motion conditions.

Abstract

Phase-shifting profilometry (PSP) enables high-accuracy 3D reconstruction but remains highly susceptible to object motion. Although numerous studies have explored compensation for motion-induced errors, residual inaccuracies still persist, particularly in complex motion scenarios. In this paper, we propose a robust phase-shifting profilometry for arbitrary motion (RPSP-AM), including six-degrees-of-freedom (6-DoF) motion (translation and rotation in any direction), non-rigid deformations, and multi-target movements, achieving high-fidelity motion-error-free 3D reconstruction. We categorize motion errors into two components: 1) ghosting artifacts induced by image misalignment, and 2) ripple-like distortions induced by phase deviation. To eliminate the ghosting artifacts, we perform pixel-wise image alignment based on dense optical flow tracking. To correct ripple-like distortions, we propose a high-accuracy, low-complexity image-sequential binomial self-compensation (I-BSC) method, which performs a summation of the homogeneous fringe images weighted by binomial coefficients, exponentially reducing the ripple-like distortions with a competitive computational speed compared with the traditional four-step phase-shifting method. Extensive experimental results demonstrate that, under challenging conditions such as 6-DoF motion, non-rigid deformations, and multi-target movements, the proposed RPSP-AM outperforms state-of-the-art (SoTA) methods in compensating for both ghosting artifacts and ripple-like distortions. Our approach extends the applicability of PSP to arbitrary motion scenarios, endowing it with potential for widespread adoption in fields such as robotics, industrial inspection, and medical reconstruction.