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• Accuracy of existing DOE-based 3D sensors is usually below mm-level (like the well-known Intel Realsense sensor etc.), and thus not suitable for high precision 3D sensing applications. • A binary encoded structured light pattern is designed and robust pattern feature detection and decoding algorithms are proposed. • A DOE is manufactured based on the designed pattern, and an IR laser is used as light source for pattern projection. • Experimental results showed that higher accuracy can be obtained by the proposed approach and device in comparison with 3D sensors like Realsense etc. This paper presents a compact and accurate three-dimensional (3D) sensing system that employs a diffraction optical element as a projection device. Compared with the conventional laser speckle-based 3D sensing methods, a gridline pattern is utilized instead of a dot pattern. The proposed pattern is designed according to a pseudorandom coding scheme, and eight geometrical elements are embedded into the grid cells to form a unique codeword for each defined grid-point. By extracting the grid-points with the proposed feature detector, a topological graph is established to separate each pattern element. A convolutional neural network is trained for robust identification of the projected pattern elements. Finally, a codeword-correction procedure is applied to refine the decoding results. Using the proposed system-calibration method, accurate 3D reconstruction can be realized for the decoded grid-points. The measurement of the planarity and step distance has an absolute mean error of only 0.2–0.3 mm, indicating that it is far more accurate than the measurement using classical laser speckle-based 3D sensors. To demonstrate robustness of the proposed decoding algorithms, targets with plentiful color and texture are used. The results show that most of the grid-points can be robustly detected and that complex surfaces such as human faces and bodies can be precisely reconstructed. [ABSTRACT FROM AUTHOR]

Highlights • A reference-plane-based approach is applied to estimate the principle optical axis of LED light source as well as its principle energy. • An iterative process was proposed to optimize initial system parameters, and accurate 3D reconstruction results can be obtained for various objects. • Accurate 3D reconstruction results can be obtained based on the low-cost setup composed with some LEDs and a web-camera. Abstract This paper presents a complete computational framework for the photometric stereo system composed of some LED lamps and a single web-camera. To describe the lighting condition accurately, the angular and distance attenuation factors, as well as the LED radiance property, are considered in the modeling of the light source. The calibration of the system's parameters is a critical step for our setup, and a two-step calibration procedure is proposed in this work. A multiple-sphere-based approach is first used to estimate the light source positions. Then, a reference-plane-based approach is applied to estimate the principal optical axis of each light source and its principal energy. For each surface point on the target, the direction and intensity of its incidental light ray can be precisely determined by the calibration parameters and the quasi-point light model. Based on the initial 3D reconstruction result, an iterative procedure is applied to optimize the model's parameters for each surface point with respect to its initial estimated depth. In the experiments, both regular and free-form surfaces including a real human face are used. The results show that accurate 3D reconstruction results can be obtained by the proposed approach based on the low-cost setup. [ABSTRACT FROM AUTHOR]

This paper presents a novel structured light approach for the 3D reconstruction of specular surface. The binary shifting strip is adopted as structured light pattern instead of conventional sinusoidal pattern. Based on the framework of conventional High Dynamic Range (HDR) imaging technique, an efficient means is first introduced to estimate the camera response function. And then, dynamic range of the generated radiance map is compressed in the gradient domain by introducing an attenuation function. Subject to the change of lighting conditions caused by projecting different structured light patterns, the structure light image with middle exposure level is selected as the reference image and used for the slight adjustment of the primary fused image. Finally, the regenerated structured light images with well exposing condition are used for 3D reconstruction of the specular surface. To evaluate performance of the method, some stainless stamping parts with strong reflectivity are used for the experiments. And the results showed that, different specular targets with various shapes can be precisely reconstructed by the proposed method. [ABSTRACT FROM AUTHOR]

Conventional Photometric Stereo (PS) techniques are usually based on the assumption that the light sources are assumed sufficiently far from the object that all incoming light can be modeled using parallel rays. Meanwhile, for near-field lighting conditions the light sources are close to the object so the parallel ray model cannot be used. To determine the surface normal for each point on the object more accurately, the incoming light direction should be calculated individually for each point. In this work, based on a simple PS setup consisting of LED lamps and one camera, we present a practical method for calibrating lighting directions. First, an optical model of an LED was introduced in the calibration procedure to represent the surface irradiance and image irradiance more accurately. A reference sphere was used for the calibration so that the LED optical axis could be estimated by extracting the specular points from the reference sphere. By introducing the LED emitting model, distance between the LED and the specular point along the optical axis can be calculated. Thus, the incident lighting directions for various image points can be estimated individually. To improve the estimation robustness, a non-linear fitting approach was also applied. Experiments were conducted using objects and the results are compared with traditional methods to demonstrate its feasibility and improvement. [ABSTRACT FROM AUTHOR]

Benefiting from the small size and low driven voltage of the Micro Electro Mechanical Systems (MEMS) mirror, MEMS-based structured light (SL) 3D reconstruction has recently attracted much attention. In this paper, we propose a novel triangular stereo model for uniaxial MEMS-based 3D reconstruction. Existing SL methods based on MEMS mirrors often require the construction of a look-up table(LUT), but the proposed method only requires 34 parameters for accurate reconstruction. By analyzing the anatomy of the MEMS mirror, we put forward a transition function that allows the MEMS mirror to be regarded as an inverse camera model. Then, the triangular stereo principle can be directly employed to calculate 3D information. Furthermore, we present a calibration method to obtain the parameters of our model, since MEMS mirrors can only perform unidirectional fringe projection. Extensive experiments are performed to verify the feasibility and accuracy of our proposed mathematical model and calibration method. [ABSTRACT FROM AUTHOR]

Decoding is a challenging and complex problem in a coded structured light system. In this paper, a robust pattern decoding method is proposed for the shape-coded structured light in which the pattern is designed as grid shape with embedded geometrical shapes. In our decoding method, advancements are made at three steps. First, a multi-template feature detection algorithm is introduced to detect the feature point which is the intersection of each two orthogonal grid-lines. Second, pattern element identification is modelled as a supervised classification problem and the deep neural network technique is applied for the accurate classification of pattern elements. Before that, a training dataset is established, which contains a mass of pattern elements with various blurring and distortions. Third, an error correction mechanism based on epipolar constraint, coplanarity constraint and topological constraint is presented to reduce the false matches. In the experiments, several complex objects including human hand are chosen to test the accuracy and robustness of the proposed method. The experimental results show that our decoding method not only has high decoding accuracy, but also owns strong robustness to surface color and complex textures. [ABSTRACT FROM AUTHOR]

• The curved LCD is first applied to the PMD, which increases the measurable curvature than the planar LCD. • A calibration method is proposed for the system based on the 3D fiducials on the curved LCD rather than the 2D fiducials on the planar one. • Different from the traditional stereo-PMD in which only areas that has common FOV with phase information of two cameras can be reconstructed, the proposed stereo-PMD reconstruction and registration algorithm can reconstruct the surface in FOV of each camera, respectively, and then register together. • The reconstructed error of RMS is less than 100 nm for the concave mirror of ROC 1000 mm. Phase measuring deflectometry (PMD) technique is widely used to measure the specular surface. However, the Current PMD methods are generally based on the planar LCD for the measurement, which limits the measurable curvature of the surface under test (SUT). To increase the measurable range of curvature, this paper proposes a novel PMD method by using a curved LCD monitor. A calibration method based on the cylindrical coordinate system is introduced for the proposed system calibration. To extend the measurable range further, the curved LCD is applied in stereoscopic PMD. The partial surface of SUT in the field of view (FOV) of each camera and curved LCD are reconstructed with iterative algorithm respectively, the calibration parameters as well as the seed point are used for point cloud registration. Simulations show the advantage of a curved LCD over a planar one and the feasibility of the proposed method. The actual performance is demonstrated in the experiments for specular optics and a phone touchscreen. [ABSTRACT FROM AUTHOR]

When a coded strip-patterns image (CSI) is captured in a structured light system (SLs), it often suffers from low visibility at low exposure settings. Besides degrading the visual perception of the CSI, this poor quality also significantly affects the performance of 3D model reconstruction. Most of the existing image-enhanced methods, however, focus on processing natural images but not CSI. In this paper, we propose a novel and effective CSI enhancer (CSIE) designed for SLs. More concretely, a bidirectional perceptual consistency (BPC) criterion, including relative grayscale (RG), exposure, and texture level priors, is first introduced to ensure visual consistency before and after enhancement. Then, constrained by BPC, the optimization function estimates solutions of illumination with piecewise smoothness and reflectance with detail preservation. With well-refined solutions, CSIE results can be achieved accordingly and further improve the details performance of 3D model reconstruction. Experiments on multiple sets of challenging CSI sequences show that our CSIE outperforms the existing used for natural image-enhanced methods in terms of 2D enhancement, point clouds extraction (at least 17% improvement), and 3D model reconstruction. [ABSTRACT FROM AUTHOR]