Showing papers by "Yongtian Wang published in 2021"

Optical secret sharing with cascaded metasurface holography

Abstract: Secret sharing is a well-established cryptographic primitive for storing highly sensitive information like encryption keys for encoded data. It describes the problem of splitting a secret into different shares, without revealing any information about the secret to its shareholders. Here, we demonstrate an all-optical solution for secret sharing based on metasurface holography. In our concept, metasurface holograms are used as spatially separable shares that carry an encrypted message in form of a holographic image. Two of these shares can be recombined by bringing them close together. Light passing through this stack of metasurfaces accumulates the phase shift of both holograms and can optically reconstruct the secret with high fidelity. On the other hand, the holograms generated by the single metasurfaces can be used for identifying each shareholder. Furthermore, we demonstrate that the inherent translational alignment sensitivity between the two stacked metasurface holograms can be used for spatial multiplexing, which can be further extended to realize optical rulers.

Design and manufacture AR head-mounted displays: A review and outlook

Abstract: Augmented reality head-mounted displays (AR-HMDs) enable users to see real images of the outside world and visualize virtual information generated by a computer at any time and from any location, making them useful for various applications. The manufacture of AR-HMDs combines the fields of optical engineering, optical materials, optical coating, precision manufacturing, electronic science, computer science, physiology, ergonomics, etc. This paper primarily focuses on the optical engineering of AR-HMDs. Optical combiners and display devices are used to combine real-world and virtual-world objects that are visible to the human eye. In this review, existing AR-HMD optical solutions employed for optical combiners are divided into three categories: optical solutions based on macro-, micro-, and nanooptics. The physical principles, optical structure, performance parameters, and manufacturing process of different types of AR-HMD optical solutions are subsequently analyzed. Moreover, their advantages and disadvantages are investigated and evaluated. In addition, the bottlenecks and future development trends in the case of AR-HMD optical solutions are discussed.

Generation of Airy beam arrays in real and K spaces based on a dielectric metasurface

Abstract: Airy beams are widely used in various optical devices and optical experiments owing to their unique characteristics such as self-acceleration, self-recovery, and non-diffraction. Here we designed and demonstrated a metasurface capable of encoding two phase distributions independently in dual circular polarization channels. We experimentally observed the generated Airy beam arrays loaded on the metasurface in the real and K spaces. Compared with the traditional method, such method provides a more efficient solution to generate large capacity Airy beam arrays with switchable working modes in the broadband spectrum. The results may pave the way for the integration and miniaturization of micro-nano devices and provide a platform for information processing, particle manipulation, space–time optical wave packets, and Airy lasers.

Nonlinear bicolor holography using plasmonic metasurfaces

Abstract: Nonlinear metasurface holography shows the great potential of metasurfaces to control the phase, amplitude, and polarization of light while simultaneously converting the frequency of the light. The possibility of tailoring the scattering properties of a coherent beam, as well as the scattering properties of nonlinear signals originating from the meta-atoms facilitates a huge degree of freedom in beam shaping application. Recently, several approaches showed that virtual objects or any kind of optical information can be generated at a wavelength different from the laser input beam. Here, we demonstrate a single-layer nonlinear geometric-phase metasurface made of plasmonic nanostructures for a simultaneous second and third harmonic generation. Different from previous works, we demonstrate a two-color hologram with dissimilar types of nanostructures that generate the color information by different nonlinear optical processes. The amplitude ratio of both harmonic signals can be adapted depending on the nanostructures' resonance as well as the power and the wavelength of the incident laser beam. The two-color holographic image is reconstructed in the Fourier space at visible wavelengths with equal amplitudes using a single near-infrared wavelength. Nonlinear holography using multiple nonlinear processes simultaneously provides an alternative path to holographic color display applications, enhanced optical encryption schemes, and multiplexed optical data-storage.

Optical secret sharing with cascaded metasurface holography.

Abstract: Secret sharing is a well-established cryptographic primitive for storing highly sensitive information like encryption keys for encoded data. It describes the problem of splitting a secret into different shares, without revealing any information to its shareholders. Here, we demonstrate an all-optical solution for secret sharing based on metasurface holography. In our concept, metasurface holograms are used as spatially separable shares that carry encrypted messages in the form of holographic images. Two of these shares can be recombined by bringing them close together. Light passing through this stack of metasurfaces accumulates the phase shift of both holograms and optically reconstructs the secret with high fidelity. In addition, the hologram generated by each single metasurface can uniquely identify its shareholder. Furthermore, we demonstrate that the inherent translational alignment sensitivity between two stacked metasurface holograms can be used for spatial multiplexing, which can be further extended to realize optical rulers.

Acoustic geometric-phase meta-array

Abstract: Metasurfaces based on geometric phase acquired from the conversion of the optical spin states provide a robust control over the wavefront of light, and have been widely employed for construction of various types of functional metasurface devices. However, this powerful approach cannot be readily transferred to the manipulation of acoustic waves because acoustic waves do not possess the spin degree of freedom. Here, we propose the concept of acoustic geometric-phase meta-array by leveraging the conversion of orbital angular momentum of acoustic waves, where well-defined geometric-phases can be attained through versatile topological charge conversion processes. This work extends the concept of geometric-phase metasurface from optics to acoustics, and provides a new route for acoustic wave control.

Design of a near-eye display measurement system using an anthropomorphic vision imaging method.

Abstract: We developed a new near-eye display measurement system using anthropomorphic vision imaging to measure the key parameters of near-eye displays, including field-of-view (FOV), angular resolution, eye box, and virtual image depth. The characteristics of the human eye, such as pupil position, pupil size variation, accommodation function, and the high resolution of the fovea, are imitated by the proposed measurement system. A FOV scanning structure, together with a non-vignetting image-telecentric lens system, captures the virtual image from the near-eye display by imitating human eye function. As a proof-of-concept, a prototype device was used to obtain large-range, high-resolution measurements for key parameters of near-eye displays.

Local-global active contour model based on tensor-based representation for 3D ultrasound vessel segmentation.

Abstract: Three-dimensional (3D) vessel segmentation can provide full spatial information about an anatomic structure to help physicians gain increased understanding of vascular structures, which plays an utmost role in many medical image-processing and analysis applications. The purpose of this paper aims to develop a 3D vessel-segmentation method that can improve segmentation accuracy in 3D ultrasound images. We propose a 3D tensor-based active contour model method for accurate 3D vessel segmentation. With our method, the contrast-independent multiscale bottom-hat tensor representation and local-global information are captured. This strategy ensures the effective extraction of the boundaries of vessels from inhomogeneous and homogeneous regions without being affected by the noise and low-contrast of the 3D ultrasound images. Experimental results in clinical 3D ultrasound and public 3D Multiphoton Microscopy datasets are used for quantitative and qualitative comparison with several state-of-the-art vessel segmentation methods. Clinical experiments demonstrate that our method can achieve a smoother and more accurate boundary of the vessel object than competing methods. The mean SE, SP and ACC of the proposed method are: 0.7768±0.0597, 0.9978±0.0013 and 0.9971±0.0015 respectively. Experiments on the public dataset show that our method can segment complex vessels in different medical images with noise and low- contrast.

Optical distortion correction considering radial and tangential distortion rates defined by optical design

Abstract: This paper proposes a high-accuracy distortion correction method for optical imaging distortion mapping and computational image predistortion. Due to the establishment of the predistortion is based on the distortion evaluation in the common optical design software CODE V, it can be used in the broad field of optical imaging system. Two distortion correction methods considering radial and tangential distortion rates which defined by optical design are introduced to perform distortion correction, and the forward and inverse image warping interpolation methods are adopted, separately. Simulations are conducted to verify the effectiveness in correcting complex distortion for freeform off-axis optical system. Furthermore, we implement a distortion correction experiment for an augmented reality head-mounted display that suffers from an asymmetric distortion with the maximum tangential distortion over 7%. For the first method, fast and high-accuracy image warping is achieved, and the RMS error of the approximation predistortion image is less than 1 pixel. Meanwhile, the RMS errors of the corrected imaging points are approximately 1.93 pixels vertically and 2.16 pixels horizontally when using a 5-megapixel camera. The second method considers the additional influence of the actual machining and assembly errors of the optical system, and the RMS errors of 0.89 pixels vertically and 0.85 pixels horizontally are achieved.

Design of a miniature anamorphic lens with a freeform front group and an aspheric rear group

Abstract: We propose a miniature anamorphic lens design that records wide-screen videos on an ordinary CMOS format. The front group consists of two freeform lenses, which achieve different focal lengths in the two orthogonal directions and thus enable the anamorphic characteristics. The rear group is made of rotationally symmetric aspheric elements that relay the image on the sensor. The annularly stitched extreme-point-based polynomial surface description is proposed to control the extreme point position and the air clearance between elements in the optimization process. An optimization method based on surface upgrade and conversion is adopted in the design. The design result offers an anamorphic ratio of 1.33 and an f-number (f / #) of ∼2, with a field of view of 65.3 deg × 35 deg. The overall length of the lens is 9.5 mm, which shows an advantage for integration into pocket devices.

Nonlinear Bicolor Holography Using Plasmonic Metasurfaces.

Abstract: Nonlinear metasurface holography shows the great potential of metasurfaces to control the phase, amplitude, and polarization of light while simultaneously converting the frequency of the light. The...

Freeform beam splitting system design for generating an array of identical sub-beams

Abstract: Laser beam splitting by freeform optics is promising but less studied. Instead of directly forming a target spot array, we propose to first convert the input beam into a closely connected Gaussian sub-beam array. All the Gaussian sub-beams have the same optical field distributions which thus can produce identical discrete spots on the target plane. Such a design concept is very beneficial to ensure the consistency for laser processing. Importantly, the introduction of an intermediate Gaussian sub-beam array can reduce diffraction effects when the size of each Gaussian sub-beam is sufficiently larger than that of the corresponding sub-area within the input beam. The desired transformation can be achieved by two typical systems. The first system consists of two plano-freeform lenses. The second system is composed of a plano-freeform lens and a lens with an entrance freeform surface and an exit surface of freeform lens array. The two freeform beam splitting systems can be determined based on appropriate ray mappings among the input, intermediate and target irradiance distributions and a subsequent double-surface construction. Geometrical and physical simulations verify the effectivenesses of the two beam splitting systems.

Novel Augmented Reality System for Oral and Maxillofacial Surgery.

Abstract: Recently, in the field of surgical visualization, augmented reality technology has shown incomparable advantages in oral and maxillofacial surgery. However, the current augmented reality methods need to develop personalized occlusal splints and perform secondary Computed Tomography (CT) scanning. These unnecessary preparations lead to high cost and extend the time of preoperative preparation. In this paper, we propose an augmented reality surgery guidance system based on 3D scanning. The system innovatively designs a universal occlusal splint for all patients and reconstructs the virtual model of patients with occlusal splints through 3D scanning. During the surgery, the pose relationship between the virtual model and the markers is computed through the marker on the occlusal splint. The proposed method can replace the wearing of occlusal splints for the secondary CT scanning during surgery. Experimental results show that the average target registration error of the proposed method is \(\text{1.38}\pm \text{0.43 mm}\), which is comparable to the accuracy of the secondary CT scanning method. This result suggests the great application potential and value of the proposed method in oral and maxillofacial surgery.

Single Scene Image Editing Based on Deep Intrinsic Decomposition

Abstract: Intrinsic decomposition is an inherent problem in computer graphics and computer vision, which decomposes an image into a reflectance image and a shading image. Through the processing of reflectance and shading, it can achieve the image scene editing effect consistent with the vision of the real scene, which endows application potentials to augmented reality. In this paper, we propose a convolutional neural network structure that includes shared and independent encoder to the independent decoder as well as several different loss functions for training based on the assumption of intrinsic decomposition and differences in datasets. To address the shortcomings of the existing synthetic dataset, we reconstruct the new synthetic data and train our network on the synthetic and real datasets in sequence. We quantitatively and qualitatively evaluate our intrinsic decomposition results on the IIW dataset, and the result shows that they outperform those of existing methods. We also perform image editing based on our deep intrinsic decomposition on images of real different scenes and obtain satisfactory visual results.

Analysis of teenagers' preferences and concerns regarding HMDs in education

Abstract: Background Virtual reality (VR) has become a powerful and promising tool for education, and numerous studies have investigated the application and effectiveness of VR education. However, few studies have focused on the expectations and concerns of teenagers regarding head-mounted displays (HMDs), which are used for this purpose. Methods In this paper, we aim to explore the current problems and necessary advancements required in VR education based on a survey of 163 senior high school students who experience VR educational content for 1h. The usability and comfort of the HMD system, the physical and psychological effects on the students, and their preferences and concerns are investigated. Results The results show that HMDs increase students' interest, concentration, and enthusiasm for learning. However, isolated virtual environments make students feel nervous and afraid. The immersive environment also makes them worry about VR addiction and confusing the physical world with the virtual one. Conclusions VR has great potential in the field of education, but the issue of safety needs to be considered in the future.

Cross-Domain Transfer Learning for Vessel Segmentation in Computed Tomographic Coronary Angiographic Images.

Abstract: Segmenting coronary arteries in computed tomographic angiography images is an essential procedure for coronary artery disease diagnosis. However, it still remains challenging due to the insufficient annotation data for supervised deep learning methods. To solve this problem, we propose a novel cross-domain transfer learning network to adaptively transfer knowledge learned from public liver vessel dataset for coronary artery segmentation. The signed distance map learning task is joined to enforce the network to transfer tubular structure knowledge from the liver vessel. Moreover, an adaptive feature-selection module is used to determine the optimal fine-tune strategy for every target sample. We conduct ablation experiments to demonstrate the effectiveness of the auxiliary task and module. We also compare the proposed method with other state-of-the-art transfer learning and segmentation methods. Results showed that our method achieve the best performance on accurate coronary artery segmentation. Our method achieves the best Dice score of 81.60%, an improvement of at least 1% with respect to other methods.

Pretrained Self-supervised Material Reflectance Estimation Based on a Differentiable Image-Based Renderer

Abstract: Measuring the material reflectance of surfaces is a key technology in inverse rendering, which can be used in object appearance reconstruction. In this paper we propose a novel deep learning-based method to extract material information represented by a physically-based bidirectional reflectance distribution function from an RGB image of an object. Firstly, we design new deep convolutional neural network architectures to regress material parameters by self-supervised training based on a differentiable image-based renderer. Then we generate a synthetic dataset to train the model as the initialization of the self-supervised system. To transfer the domain from the synthetic data to the real image, we introduce a test-time training strategy to finetune the pretrained model to improve the performance. The proposed architecture only requires one image as input and the experiments are conducted to evaluate the proposed method on both the synthetic data and real data. The results show that our trained model presents dramatic improvement and verifies the effectiveness of the proposed methods.

A New Dataset and Recognition for Egocentric Microgesture Designed by Ergonomists.

Abstract: Virtual and Augmented reality (VR/AR) are widely deployed in industrial, medical, educational, and entertaining fields. The design of interactive interfaces has an impact on usability, comfort, and efficiency. Hand controllers and gestures are popularly used in VR/AR devices. However, users may suffer from overloading on the upper extremities while raising the hand or controller. Therefore, we released a microgesture library with 19 microgestures designed by ergonomists. Users can perform microgestures for an extended duration by resting the forearm on the tables to reduce the load on the upper extremity. Additionally, we collected a microgesture dataset of 2900 samples and utilized the C3D model to recognize the microgesture dataset. Finally, we achieved a recognition accuracy of 93.4% on the microgestures dataset.

Compact magnetic field sensor based on plasmonic fiber-tip

Abstract: A plasmonic fiber-tip based on the metallic metasurface and the multimode fiber (MMF) alleviates the limitation of the inevitable large sensing size caused by fiber side wall functionalization. Localized surface plasmon resonance (LSPR) based on metasurface on the fiber-tip provides a promising way to manipulate and interrogate the transmitted and reflection light in sub-wavelength range. Combining the advantages of plasmonic fiber-tip and magnetic fluid, a compact magnetic field fiber-optic sensor is proposed and verified by experiments. The developed fiber-optic magnetic field sensor has linear response and high magnetic strength sensitivity of 0.532 nm/mT over a range of 0-20 mT. In addition, the results also prove the feasibility of pseudo-vector magnetic field sensing.