Structured light (SL) has a trade-off between acquisition time and spatial resolution. Temporally coded SL can produce a 3D reconstruction with high density, yet it is not applicable to dynamic reconstruction. On the contrary, spatially coded SL works with a single shot, but it can only achieve sparse reconstruction. This paper aims to achieve accurate 3D dense and dynamic reconstruction at the same time. A speckle-based SL sensor is presented, which consists of two cameras and a diffractive optical element (DOE) projector. The two cameras record images synchronously. First, a speckle pattern was elaborately designed and projected. Second, a high-accuracy calibration method was proposed to calibrate the system; meanwhile, the stereo images were accurately aligned by developing an optimized epipolar rectification algorithm. Then, an improved semi-global matching (SGM) algorithm was proposed to improve the correctness of the stereo matching, through which a high-quality depth map was achieved. Finally, dense point clouds could be recovered from the depth map. The DOE projector was designed with a size of 8 mm × 8 mm. The baseline between stereo cameras was controlled to be below 50 mm. Experimental results validated the effectiveness of the proposed algorithm. Compared with some other single-shot 3D systems, our system displayed a better performance. At close range, such as 0.4 m, our system could achieve submillimeter accuracy.
DENSE 3D OBJECT RECONSTRUCTION USING STRUCTURED-LIGHT SCANNER AND DEEP LEARNING