Precise 3-D surface reconstruction plays an important role in automated manipulation, industrial inspection, robotics, and so on. In this article, we present a novel 3-D surface reconstruction framework for stereo vision systems assisted with structured light projection. In the framework, a multistep matching scheme is proposed to establish a reliable correspondence between image pairs with high computation efficiency and accuracy. The successive matching steps can find the most precise correspondence through a step-by-step filtering procedure. To further enhance the precision, a correspondence refinement algorithm is presented. Phase maps with different frequencies are utilized as the code words for the multistep matching due to their high encoding accuracy and robustness to noise. This method does not require phase unwrapping or projector calibration, which improves the reconstruction precision and simplifies the operation. Selection strategies for the number of matching steps, the pattern frequencies, and the matching threshold are proposed. Furthermore, various 3-D reconstruction experiments are conducted using the proposed framework. Comparative experiments verify the advantages of the proposed framework compared with existing 3-D reconstruction methods regarding the accuracy and precision. The adaptability to scenarios with different motion speeds is demonstrated. Robustness and limitations of the framework are also revealed by conducting experiments in challenging scenarios. Note to Practitioners —This article is motivated by the precise 3-D surface reconstruction problem in automated robotic systems. In different scenarios, such as the reconstruction of the static objects or moving objects, the errors induced by sensor noise and motion should be taken into consideration. To enhance the measurement precision under these occasions, selection of pattern number and fringe frequencies has been a problem. To overcome these problems, this article proposes a novel framework for active stereo 3-D surface reconstruction. The framework utilizes multifrequency phase-shifting fringes to encode the reconstructed target. Then, a multistep matching method filters the candidates step by step to obtain the most precise corresponding pixel and avoid noise error accumulation. A refinement method is introduced to further improve the precision. Selection strategies of the number of matching steps, the fringe frequencies, and matching thresholds enable the 3-D reconstruction framework to be utilized on different occasions. In applications, limitations of the proposed method should be noted.

中文翻译：

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使用多步匹配的主动立体3-D表面重建

精确的3D表面重建在自动化操作，工业检查，机器人技术等方面起着重要作用。在本文中，我们为立体视觉系统提供了一种新颖的3-D表面重建框架，该框架具有结构化的光投射。在该框架中，提出了一种多步匹配方案，以建立图像对之间的可靠对应关系，具有较高的计算效率和准确性。连续的匹配步骤可以通过逐步过滤过程找到最精确的对应关系。为了进一步提高精度，提出了一种对应改进算法。具有不同频率的相位图由于其高编码精度和抗噪声能力而被用作多步匹配的代码字。该方法不需要相位展开或投影仪校准，从而提高了重建精度并简化了操作。提出了匹配步数，码型频率和匹配阈值的选择策略。此外，使用提出的框架进行了各种3-D重建实验。比较实验证明，与现有的3-D重建方法相比，该方法在准确性和精度上具有优势。展示了对具有不同运动速度的场景的适应性。通过在具有挑战性的场景中进行实验，还揭示了框架的鲁棒性和局限性。提出了模式频率和匹配阈值。此外，使用提出的框架进行了各种3-D重建实验。比较实验证明，与现有的3-D重建方法相比，该方法在准确性和精度上具有优势。展示了对具有不同运动速度的场景的适应性。通过在具有挑战性的场景中进行实验，还揭示了框架的鲁棒性和局限性。提出了模式频率和匹配阈值。此外，使用提出的框架进行了各种3-D重建实验。比较实验证明，与现有的3-D重建方法相比，该方法在准确性和精度上具有优势。展示了对具有不同运动速度的场景的适应性。通过在具有挑战性的场景中进行实验，还揭示了框架的鲁棒性和局限性。展示了对具有不同运动速度的场景的适应性。通过在具有挑战性的场景中进行实验，还揭示了框架的鲁棒性和局限性。展示了对具有不同运动速度的场景的适应性。通过在具有挑战性的场景中进行实验，还揭示了框架的鲁棒性和局限性。执业者注意 —本文受到自动化机器人系统中精确的3D表面重建问题的启发。在不同的场景中，例如重建静态对象或移动对象时，应考虑由传感器噪声和运动引起的误差。为了在这种情况下提高测量精度，选择图案编号和条纹频率一直是个问题。为了克服这些问题，本文提出了一种用于主动立体3-D表面重建的新颖框架。该框架利用多频相移条纹对重建的目标进行编码。然后，多步匹配方法逐步过滤候选对象，以获得最精确的对应像素并避免噪声误差累积。引入了一种改进方法以进一步提高精度。匹配步骤数，边缘频率和匹配阈值的选择策略使3-D重建框架可以在不同情况下使用。在应用中，应注意所提出方法的局限性。