We present an adaptive phase unwrapping method based on geometric constraints and the gradient field without additional images for high-speed three-dimensional (3D) shape measurement. Specifically, we reconstruct the 3D geometry of moving objects frame by frame. We first create a reference phase map at the depth provided by the former frame. Then we optimize the depth value by validating the continuity of the computed unwrapped phase based on the modulus of the gradient field and recalculate the correct absolute phase map with the optimal depth value. After reconstructing the 3D geometry of the current frame, 3D data are delivered to the next frame. In particular, a geometric constraint-based method is applied in the first frame. Experiment results indicate that our approach, which requires only three phase-shifted fringe patterns per frame, can measure moving objects with high accuracy and robustness. Additionally, several isolated objects can also be measured by our method if they are continuous.
This paper presents a novel method for measuring the size of standard cylinders with the LiDAR and RGB sensors embedded with iPhones. First, we reconstruct 3D points of cylindrical surfaces using the LiDAR data. With 3D point cloud data, we fit the orientation of the cylinder with center pixels. Since the LiDAR does not offer 3D points with high resolution nor high accuracy, we select a segment of the point cloud data and compute the average depth of these segment pixels as the distance from the cylinder to the camera. We then compute the diameter by the geometric relationship of each point on the cylinder. Finally, we improve the measurement accuracy by applying a estimation function. Experimental results show that at distances from 0.3 m to 2 m with different tilt angles, the proposed method can achieve 3 cm cylinder diameter measurement accuracy for the cylinders with a diameter of 8 cm and 14 cm, and 5 cm accuracy for the cylinder with a diameter of 22 cm.
We developed a novel method based on geometry to reconstruct a dynamic face solely by using the conventional structured light system, which does not need extra images, hardware components, or objects. In our method, the bridge of the nose is considered the feature region because its shape remains almost constant when a human is moving or making expressions. This three-dimensional (3D) face reconstruction method consists of the following steps: (1) spatially unwrap the phase and obtain the texture image for each frame; (2) locate the nose area for each frame with a feature detection algorithm; (3) determine the fringe order in the first frame with the cues given by traditional methods and acquire the recovered result of the feature region; (4) locate the feature region for each possible fringe order in one frame by finding the pixel nearest to the camera along the depth direction in the nose area; (5) register each 3D shape of the feature region with it in the former frame by the Iterative Closest Point (ICP) algorithm; (6) determine the fringe order by the minimal Hausdorff distance between two registered 3D shapes and then construct the face with the entire absolute phase map. Experimental results indicate that our proposed approach is capable of real-time reconstruction of a dynamic face and only three phase-shifted fringes are required per frame.
KEYWORDS: Cameras, Video, Projection systems, Algorithm development, 3D image processing, 3D modeling, Phase shifts, Stereoscopy, Real time imaging, 3D metrology
This paper presents a novel method that does not reqire additional images for 3D video imaging with phase unwrapping technique using geometric constrain based on graident field. Specifically, we creat an artificial absolute phase map Φmin at given depth z = zmin from the former frame. We optimize the zmin by validate the continuity of computed unwrapped phase with gradient field and deliver the true minimum z value zmin to next frame. The first frame is reconstructed by a static method. Experiments demonstrate that only three phase-shifted fringe patterns are required to measure moving objects.
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