Active Stereo 3-D Surface Reconstruction Using Multistep Matching

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.