Epipolar Geometry Guided Highly Robust Structured Light 3D Imaging

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Abstract
Structured light (SL) based three-dimensional (3D) imaging technology has been widely employed in many fields of computer vision. However, currently available SL based depth sensors are sensitive to imaging noises, which severely limits the performance of subsequent advanced vision tasks. In this letter, we propose a robust and practical SL illumination pattern coding method based on epipolar geometry. The proposed pattern can effectively alleviate coding redundancy in traditional global random speckle SL patterns and make the stereo matching more robust to noise. Meanwhile, this coding strategy supplies sufficient non-local similar blocks, which inspires us to propose a uni-direction block-stacking 3D filtering algorithm to further improve the 3D imaging quality. To verify the proposed algorithms, we developed a prototype using the off-the-shelf projector and camera. Both simulation and real scene experimental results show that the proposed methods can achieve high-quality 3D imaging performance under different noisy conditions.

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