Showing papers by "Yongtian Wang published in 2015"

Teaching based on augmented reality for a technical creative design course

Abstract: Student creativity is currently attracting considerable attention. An increasing number of high schools in China are trying to improve the learning motivation and creativity of students, as well as the teaching efficiency of creative design, by introducing augmented reality (AR) technology into creative design courses. However, many teachers have only limited knowledge of AR, and software developers are not familiar with general creative design education, which makes it difficult to incorporate AR in such courses. In many high schools in China, the lack of relevant teaching facilities and creative design equipment means that the environment in which the technology curriculum is applied still has a long way to go to meet the real requirement of curriculum. To address these problems, we present a general technical creative design teaching scheme that includes AR. Our approach is based on the ARCS model of motivational design, social psychology, and a computational model of creativity. Two teaching aids are introduced to support this teaching scheme: "AR Creative-Classroom," which explains the domain-relevant knowledge of creative design, and "AR Creative-Builder," which helps students to build actual AR scenes. The results of a pilot study show that the proposed teaching scheme significantly improves learning motivation, student creativity, and the teaching of creative design. Design a creative design teaching scheme with the introduction of AR.Develop two AR-based and teaching scheme related teaching aids.Demonstrate the AR-based teaching scheme improves the learning motivation.Demonstrate the scheme helps students to experience the complete creative design process.Demonstrate the AR-based teaching scheme improve the creativity of the outputs.

Pushing the resolution of photolithography down to 15nm by surface plasmon interference.

Abstract: A deep ultraviolet plasmonic structure is designed and a surface plasmon interference lithography method using the structure is proposed to generate large-area periodic nanopatterns. By exciting the anti-symmetric coupled surface plasmon polaritons in the structure, ultrahigh resolution periodic patterns can be formed in a photoresist. The resolution of the generated patterns can be tuned by changing the refractive index and thickness of the photoresist. We demonstrate numerically that one-dimensional and two-dimensional patterns with a half-pitch resolution of 14.6 nm can be generated in a 25 nm-thick photoresist by using the structure under 193 nm illumination. Furthermore, the half-pitch resolution of the generated patterns can be down to 13 nm if high refractive index photoresists are used. Our findings open up an avenue to push the half-pitch resolution of photolithography towards 10 nm.

Brain MR image denoising for Rician noise using pre-smooth non-local means filter

Abstract: Magnetic resonance imaging (MRI) is corrupted by Rician noise, which is image dependent and computed from both real and imaginary images. Rician noise makes image-based quantitative measurement difficult. The non-local means (NLM) filter has been proven to be effective against additive noise. Considering the characteristics of both Rician noise and the NLM filter, this study proposes a frame for a pre-smoothing NLM (PSNLM) filter combined with image transformation. In the PSNLM frame, noisy MRI is first transformed into an image in which noise can be treated as additive noise. Second, the transformed MRI is pre-smoothed via a traditional denoising method. Third, the NLM filter is applied to the transformed MRI, with weights that are computed from the pre-smoothed image. Finally, inverse transformation is performed on the denoised MRI to obtain the denoising results. To test the performance of the proposed method, both simulated and real patient data are used, and various pre-smoothing (Gaussian, median, and anisotropic filters) and image transformation [squared magnitude of the MRI, and forward and inverse variance-stabilizing trans-formations (VST)] methods are used to reduce noise. The performance of the proposed method is evaluated through visual inspection and quantitative comparison of the peak signal-to-noise ratio of the simulated data. The real data include Alzheimer’s disease patients and normal controls. For the real patient data, the performance of the proposed method is evaluated by detecting atrophy regions in the hippocampus and the parahippocampal gyrus. The comparison of the experimental results demonstrates that using a Gaussian pre-smoothing filter and VST produce the best results for the peak signal-to-noise ratio (PSNR) and atrophy detection.

Quantitative Analysis of Deformable Model-Based 3-D Reconstruction of Coronary Artery From Multiple Angiograms

Abstract: Three-dimensional (3-D) reconstruction of the coronary artery is important for the diagnosis and interventional treatment of cardiovascular diseases. In this paper, a novel mean composited external force back-projective composition model is proposed and integrated into the deformable model framework for the 3-D reconstruction of coronary arteries from multiple angiograms. The parametric snake evolves toward the real vascular centerline in 3-D space based on the integrated internal energy and composited external energy. In addition, a polynomial function is constructed to determine the diameter of the cross section of the vascular segments, which fully utilizes the back-projection information of multiple angiograms. The deformable and proposed methods are comparatively validated using phantom datasets and routine angiographic images with respect to space and reprojection Euclidean distance errors. The experimental results demonstrate the effectiveness and robustness of the proposed model, which can achieve a mean space error of 0.570 mm and a mean reprojection error of 0.351 mm. In addition, the influence of the angle difference to the reconstruction accuracy is discussed and validated on phantom datasets, which demonstrate that an angle difference of for any two angiograms is suitable for the 3-D reconstruction process.

Improved holographic waveguide display system

Abstract: An improved achromatic holographic waveguide display system with high efficiency is proposed, which is composed of an in-coupled planar hologram and an outcoupled volume hologram. The efficiency is improved, compared with the previous system proposed by Shi et al. (Appl. Opt.51, 4703–4078 [2012]10.1364/AO.51.004703APOPAI1559-128X), and the loss resulting from multiple exposures is reduced by the combination of the planar hologram and the volume hologram. The basic idea and principles are described, and the experiments are performed. The experimental results demonstrate that the improved system can achieve higher diffraction efficiency and reduce the experimental complexity of multiple exposures. It could be a potential method for improving the efficiency and correcting the chromatic dispersion in the waveguide display systems.

Fast multi-scale feature fusion for ECG heartbeat classification

Abstract: Electrocardiogram (ECG) is conducted to monitor the electrical activity of the heart by presenting small amplitude and duration signals; as a result, hidden information present in ECG data is difficult to determine. However, this concealed information can be used to detect abnormalities. In our study, a fast feature-fusion method of ECG heartbeat classification based on multi-linear subspace learning is proposed. The method consists of four stages. First, baseline and high frequencies are removed to segment heartbeat. Second, as an extension of wavelets, wavelet-packet decomposition is conducted to extract features. With wavelet-packet decomposition, good time and frequency resolutions can be provided simultaneously. Third, decomposed confidences are arranged as a two-way tensor, in which feature fusion is directly implemented with generalized N dimensional ICA (GND-ICA). In this method, co-relationship among different data information is considered, and disadvantages of dimensionality are prevented; this method can also be used to reduce computing compared with linear subspace-learning methods (PCA). Finally, support vector machine (SVM) is considered as a classifier in heartbeat classification. In this study, ECG records are obtained from the MIT-BIT arrhythmia database. Four main heartbeat classes are used to examine the proposed algorithm. Based on the results of five measurements, sensitivity, positive predictivity, accuracy, average accuracy, and t-test, our conclusion is that a GND-ICA-based strategy can be used to provide enhanced ECG heartbeat classification. Furthermore, large redundant features are eliminated, and classification time is reduced.

Adaptive Mesh Expansion Model (AMEM) for liver segmentation from CT image.

Abstract: This study proposes a novel adaptive mesh expansion model (AMEM) for liver segmentation from computed tomography images. The virtual deformable simplex model (DSM) is introduced to represent the mesh, in which the motion of each vertex can be easily manipulated. The balloon, edge, and gradient forces are combined with the binary image to construct the external force of the deformable model, which can rapidly drive the DSM to approach the target liver boundaries. Moreover, tangential and normal forces are combined with the gradient image to control the internal force, such that the DSM degree of smoothness can be precisely controlled. The triangular facet of the DSM is adaptively decomposed into smaller triangular components, which can significantly improve the segmentation accuracy of the irregularly sharp corners of the liver. The proposed method is evaluated on the basis of different criteria applied to 10 clinical data sets. Experiments demonstrate that the proposed AMEM algorithm is effective and robust and thus outperforms six other up-to-date algorithms. Moreover, AMEM can achieve a mean overlap error of 6.8% and a mean volume difference of 2.7%, whereas the average symmetric surface distance and the root mean square symmetric surface distance can reach 1.3 mm and 2.7 mm, respectively.

Volumetric display based on multiple mini-projectors and a rotating screen

Abstract: A method has been proposed to realize a transparent volumetric display using multiple mini-projectors and a rotating screen. Correct two-dimensional cross-sectional images are projected on a bidirectional scattering projection screen, which rotates to form a three-dimensional (3-D) image due to human vision persistence. An illumination subsystem is designed to ensure the accurate synchronization between the projectors and the rotating screen. Therefore, low-speed and low-cost miniature display devices can be used in the mini-projectors to realize dynamic volumetric imaging, which can satisfy all criteria of real 3-D vision with full color and high resolution. Experimental results of volumetric imaging realized by this method are also presented.

Design of a novel panoramic lens without central blindness

Abstract: The panoramic lenses are getting more and more popular in recent years However, these lenses have the drawback of obscuring the rays of the coaxial fields, thus cause blind area in the center field of vision We present a novel panoramic system consisting of two optical channels to overcome this issue, the system has a field of view (FOV) reaching 200 in vertical and 360 in horizontal direction without blindness area The two channels have different focal lengths, providing design flexibility to meet application requirements where the center FOV or the marginal FOV is of more interest The system has no half-reflecting surfaces to ensure high transmission ratio, but this feature greatly increase the design difficulty The distortion of the novel lens is much smaller than traditional panoramic lenses since the distortion has two node points Due to the ability of information acquisition in real-time and wide-angle, the novel panoramic lens would be very useful for a variety of real-world applications such as surveillance, short-throw projector and pilotless automobile

Omnidirectional-view three-dimensional display based on rotating selective-diffusing screen and multiple mini-projectors

Abstract: A new type of omnidirectional-view 3D display is proposed, which is composed of a rotating selective-diffusing screen and multiple mini-projectors. A selective-diffusing screen using two field lenses and one lenticular is developed and analyzed. A rotation aperture pupil structure is designed to ensure the accurate synchronization between the projectors and the rotating screen. Correct 2D images are projected on the screen by different mini-projectors, whereas the screen rotates to form the light field 3D image using the effect of human vision persistence. This method is verified by experimental results, and a touchable vivid color 3D image floating in the space above the system with correct occlusion and smooth parallax is demonstrated by the prototype.

Adaptive Tensor-Based Principal Component Analysis for Low-Dose CT Image Denoising.

Abstract: Computed tomography (CT) has a revolutionized diagnostic radiology but involves large radiation doses that directly impact image quality. In this paper, we propose adaptive tensor-based principal component analysis (AT-PCA) algorithm for low-dose CT image denoising. Pixels in the image are presented by their nearby neighbors, and are modeled as a patch. Adaptive searching windows are calculated to find similar patches as training groups for further processing. Tensor-based PCA is used to obtain transformation matrices, and coefficients are sequentially shrunk by the linear minimum mean square error. Reconstructed patches are obtained, and a denoised image is finally achieved by aggregating all of these patches. The experimental results of the standard test image show that the best results are obtained with two denoising rounds according to six quantitative measures. For the experiment on the clinical images, the proposed AT-PCA method can suppress the noise, enhance the edge, and improve the image quality more effectively than NLM and KSVD denoising methods.

PET Index of Bone Glucose Metabolism (PIBGM) Classification of PET/CT Data for Fever of Unknown Origin Diagnosis

Abstract: Objectives Fever of unknown origin (FUO) remains a challenge in clinical practice. Fluorine-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) is helpful in diagnosing the etiology of FUO. This paper aims to develop a completely automatic classification method based on PET/CT data for the computer-assisted diagnosis of FUO.

Design and fabrication of complicated diffractive optical elements on multiple curved surfaces.

Abstract: Fabrication of multiple arbitrary diffractive optical elements (DOEs) on multiple curved surfaces is always a challenge; here we propose an effective optimization method to fabricate complicated DOEs on several curved surfaces at the same time. First we design phase distribution to modulate complicated three-dimensional (3D) intensity distribution on multiple curved surfaces simultaneously, and then by exposure, the intensity distribution is transferred into the pure-phase or depth distribution. Numerical simulations and optical fabrication are performed for different intensity distributions: 3D binary patterns and 3D gray level patterns, on two or three curved surfaces, and both are in nice agreement. Since multiple DOEs are fabricated on curved surfaces simultaneously, the collimation of different curved surfaces is avoided, and it could improve the fabrication efficiency. It is expected that this proposed method would be employed in various precision 3D optical fabrication and processing in the future.

Adaptive Ridge Point Refinement for Seeds Detection in X-Ray Coronary Angiogram

Abstract: Seed point is prerequired condition for tracking based method for extracting centerline or vascular structures from the angiogram. In this paper, a novel seed point detection method for coronary artery segmentation is proposed. Vessels on the image are first enhanced according to the distribution of Hessian eigenvalue in multiscale space; consequently, centerlines of tubular vessels are also enhanced. Ridge point is extracted as candidate seed point, which is then refined according to its mathematical definition. The theoretical feasibility of this method is also proven. Finally, all the detected ridge points are checked using a self-adaptive threshold to improve the robustness of results. Clinical angiograms are used to evaluate the performance of the proposed algorithm, and the results show that the proposed algorithm can detect a large set of true seed points located on most branches of vessels. Compared with traditional seed point detection algorithms, the proposed method can detect a larger number of seed points with higher precision. Considering that the proposed method can achieve accurate seed detection without any human interaction, it can be utilized for several clinical applications, such as vessel segmentation, centerline extraction, and topological identification.

Design and fabrication of concave-convex lens for head mounted virtual reality 3D glasses

Abstract: As a kind of light-weighted and convenient tool to achieve stereoscopic vision, virtual reality glasses are gaining more popularity nowadays For these glasses, molded plastic lenses are often adopted to handle both the imaging property and the cost of massive production However, the as-built performance of the glass depends on both the optical design and the injection molding process, and maintaining the profile of the lens during injection molding process presents particular challenges In this paper, optical design is combined with processing simulation analysis to obtain a design result suitable for injection molding Based on the design and analysis results, different experiments are done using high-quality equipment to optimize the process parameters of injection molding Finally, a single concave-convex lens is designed with a field-of-view of 90° for the virtual reality 3D glasses The as-built profile error of the glass lens is controlled within 5μm, which indicates that the designed shape of the lens is fairly realized and the designed optical performance can thus be achieved

A Probabilistic Analysis of Sparse Coded Feature Pooling and Its Application for Image Retrieval.

Abstract: Feature coding and pooling as a key component of image retrieval have been widely studied over the past several years Recently sparse coding with max-pooling is regarded as the state-of-the-art for image classification However there is no comprehensive study concerning the application of sparse coding for image retrieval In this paper, we first analyze the effects of different sampling strategies for image retrieval, then we discuss feature pooling strategies on image retrieval performance with a probabilistic explanation in the context of sparse coding framework, and propose a modified sum pooling procedure which can improve the retrieval accuracy significantly Further we apply sparse coding method to aggregate multiple types of features for large-scale image retrieval Extensive experiments on commonly-used evaluation datasets demonstrate that our final compact image representation improves the retrieval accuracy significantly

11.4: Study on the Saccadic Eye Movement Metric of Visual Fatigue Induced By 3D Displays

Abstract: Developing a valid measurement of visual fatigue induced by 3D display remains a big challenge and is beneficial for optimizing the system design. In this paper, effects of 3D visual fatigue on the dynamics of saccadic eye movements are examined. Thirteen subjects participate in a random dot stereogram (RDS) based task, the performing of the task by the subjects is assumed to directly influence the level of visual fatigue that is evaluated using subjective ratings, optometric tests and eye movement indices. The results of critical fusion frequency (CFF) and accommodation measurement (ACC) show that the proposed experiment setup can induce visual fatigue. According to the subjective ratings, the visual fatigue accumulated in the experiment is mostly related to the binocular vision stress of 3D display. The peak velocity-magnitude relationship of saccadic eye movements decreases after the experiment, and no significant differences are observed in the other saccadic parameters. Our conclusion is that saccadic eye movement, particularly the peak velocity-magnitude relationship, is a sensitive indicator for visual fatigue caused by 3D display and has the potential to help the establishment of a valid on-line measure for the detection of 3D visual fatigue.

Light field acquisition using a planar catadioptric system.

Abstract: We propose a novel light field acquisition method based on a planar catadioptric system. Only one camera with a large field-of-view (FOV) is required, and multiple virtual cameras can be created via an array of planar mirrors to acquire the light field from different views. The spatial distribution of the virtual cameras can be configured flexibly to acquire particular light rays, which can be controlled by simply changing the positions of the mirrors. Compared with previous systems, no aberration or reduction in light transmittance is introduced by the planar mirrors, which ensures image quality. In this study, the design method of the planar catadioptric system is provided and a calibration procedure of its computational model is analyzed in detail. The method is verified by a prototype system, with which the correct digital refocusing results are achieved using the acquired, calibrated light field.

Wearable display apparatus

Abstract: A display apparatus includes a planar waveguide optical element, a projection optical system, and a microdisplay device. By including free-form optics and waveguide technology, the volume and weight of the display apparatus can be reduced, and an optical system can be realized with improved image quality, structure, and performance parameters.

Convex hull matching and hierarchical decomposition for multimodality medical image registration.

Abstract: This study proposes a novel hierarchical pyramid strategy for 3D registration of multimodality medical images. The surfaces of the source and target volume data are first extracted, and the surface point clouds are then aligned roughly using convex hull matching. The convex hull matching registration procedure could align images with large-scale transformations. The original images are divided into blocks and the corresponding blocks in the two images are registered by affine and non-rigid registration procedures. The sub-blocks are iteratively smoothed by the Gaussian kernel with different sizes during the registration procedure. The registration result of the large kernel is taken as the input of the small kernel registration. The fine registration of the two volume data sets is achieved by iteratively increasing the number of blocks, in which increase in similarity measure is taken as a criterion for acceptation of each iteration level. Results demonstrate the effectiveness and robustness of the proposed method in registering the multiple modalities of medical images.

Visual Fatigue Evaluation of Stereoscopic Display Based on Heart Rate Asymmetry and Ordinal Pattern Statistics

Abstract: 3D display has extensive application potential in the field of virtual reality. However, viewing 3D display for long time tends to induce users' visual fatigue such as headache, dizziness, etc. In order to improve the quality of 3D display and its user-friendliness, it's necessary to uncover the effective metrics which can detect and assess visual fatigue quantitatively and objectively. In order to solve the above-mentioned problem, a fatigue evaluation system is designed in which electrocardiogram (ECG) is studied with the analysis of heart rate asymmetry and ordinal pattern statistics. Subjects being evaluated are asked to watch 3D display for a given period of time and their ECGs are recorded in real time. The analysis of ECG shows that certain physiological indicators change significantly, the state of heart rate of the subjects watching 3D display is different from those without watching any 3D content and the distribution of ordinal pattern statistics reflects the state of visual fatigue.

Study of electroencephalography-based objective stereoscopic visual fatigue evaluation

Abstract: Stereoscopic display technology has attracted much attention owing to its important applications in many aspects of our daily life. Nevertheless, visual fatigue caused by accommodation-vergence conflict affects viewers' comfort and its evaluation remains a critical issue. A monotonous and repetitive random dot stereogram based experiment is designed to induce visual fatigue and an objective electroencephalography-based evaluation method is proposed in this paper, in which relative energy spectra of 6, a and p frequency bands are computed respectively. Such statistical analysis techniques as paired-t test and analysis of variance are applied to compare features between alert and fatigue stages and the comparison result shows that a activity changes more significantly compared with that of p and G activities. It has also been found in the experimental results that a activity shows stable significant increase with the progress of experiment, especially in the frontal site, which indicates that a wave can be a promising indicator for stereoscopic visual fatigue evaluation.

Image feature query method in combination with gravity sensor and image feature point angles

Abstract: The invention discloses an image feature query method in combination with a gravity sensor and image feature point angles. A video camera with the gravity sensor is adopted for acquiring a target image, and an image sample with gravity information is obtained. A query image and the image sample are both processed to form an overall compact vector representation of the image sample by the following steps: extracting feature points, containing the gravity information, of the image; adding an angle calculated by a formula to each of angle attributes in all the extracted feature points for rotation, and performing bag-of-word model training on all the image feature points in the rotated image to obtain a plurality of cluster centers; and performing feature encoding on all the image feature points in the rotated image, mapping the feature points to the cluster centers, performing partitioning according to the feature point angles, performing feature aggregation on each partition, and forming the overall compact vector representation. With a nearest-neighbor search method, the image sample most matched with the query image is searched for.

Omnidirectional-view three-dimensional displays using multiple mini-projectors

Abstract: We have developed omnidirectional-view 3D displays using multiple mini-projectors. Three types of synchronization structure are developed to ensure the accurate synchronization between the projectors and the rotating screen. Therefore, low-cost and low-speed display devices can be used to realize natural-looking three-dimensional (3D) scene with full color and high resolution.

Design and stray light analysis of ultra-thin geometrical waveguide

Abstract: Nowadays, the waveguide has the advantages of small thickness and light weight so that it attracts more and more attention in the field of near-eye display However, as a major problem, stray lights generated in the waveguide seriously degrade the display quality In this paper, a geometrical waveguide with a beam-splitting mirror array (BSMA) is designed by using the non-sequential ray-tracing software LightTools, and great efforts are paid to study the causes and solutions of the stray light With mass calculation and optimization based on the criterion of stray light/useful light ratio, an optimum design with the least amount of stray lights is found To further eliminate the stray light, a novel structure that couples the rays into the waveguide is designed The optimized waveguide has a FOV of 36° in the pupil-expanding direction of the waveguide, with stray light energy reduced to 1% over the useful light, the exit pupil diameter is 116mm at an eye relief of 20mm and the thickness is 24mm

A novel image representation method for liver tumor classification

Abstract: Computer aided diagnosis (CAD) has been important more than ever for accurate diagnosis of liver tumors. The paper presents a novel image representation method for classifying normal livers and livers with tumors. It starts by capturing region of interesting (ROI) for individual livers, on which patches are extracted densely. Histogram of oriented gradients (HOG) and intensity are then extracted as patch features. Taking the feature clustering centers in the training images as coding dictionary, sparse coding is used as a coding scheme for the patch extracted from both train and test images. And an effective image representation is then generated based on bag of features (BOF). In this study, an optimized coding method based on the dictionary elements nearby are utilized, which accelerate the coding procedure. The experimental results demonstrate that the proposed image representation method achieves higher classification rate.

Improved full analytical polygon-based method using Fourier analysis of 3D affine transformation

Abstract: An improved full analytical polygon-based method is proposed to speed up the computation of hologram synthesis in accordance with Fourier analysis of three-dimensional affine transformation. Numerical and Optical experiment proved the proposed method could save computation time and reconstruct three-dimensional(3D) scene precisely.

Context-Aware Based Mobile Augmented Reality Browser and its Optimization Design

Abstract: The latest research shows that despite user’s increasing interests in the Augmented Reality service, its usage frequency is low and the usage time is short. The intrinsic reason lies in its ignorance of human factors, which causes the design defect in the design stage of Augmented Reality browsers. In order to improve the quality of user experience, this paper introduces the design and optimization of a mobile Augmented Reality browser system by adopting the concept of context-aware service pushing based on scene classification, and proposes a novel interactive mode which combines Virtual Reality and Augmented Reality (AR/VR) on the basis of mental model theory. The whole design flow is verified by the design of the AR/VR hybrid interface. Experimental result shows that the proposed system of adopting hybrid interactive mode based on context-aware frameworks can not only increase the user acceptance of Augmented Reality browser, but also significantly improve quality of experiences of human-computer interaction.