Spherical Images Research Articles

A Novel Mirrored Binocular Vision Sensor Based on Spherical Catadioptric Mirrors

The binocular vision sensor composed of dual cameras is difficult to meet the requirements of synchronous image acquisition in dynamic high-speed measurement, and mirrored binocular vision sensor (MBVS) composed of single camera and catadioptric components have become popular among machine vision applications. Existing mirrored binocular vision sensors mostly comprise planar mirrors, which has the disadvantage of a small field-of-view (FOV). To extend the measurement range of the MBVS, we proposed a novel MBVS based on spherical catadioptric mirrors. The novel MBVS consists of a single camera and double spherical mirrors. The mathematical formula of the FOV of the MBVS is deduced, and the imaging light path is simulated. Then, the structural parameters of the sensor are calculated and a MBVS with a single camera and double spherical mirrors are designed. In order to preliminarily realize the distortion correction of spherical reflection imaging, the mathematical model of the MBVS is constructed. The accuracy of the calibration before and after spherical distortion correction is compared. Experimental results demonstrate the feasibility of the designed MBVS, which can extend the measurement range of the sensor.

Precision Spherical Nucleic Acids Enable Sensitive FEN1 Imaging and Controllable Drug Delivery for Cancer-Specific Therapy.

Accurate diagnosis and targeted therapy are essential to precision theranostics. However, nonspecific response of theranostic agents in healthy tissues impedes their practical applications. Here, we design an activatable DNA nanosphere for specifically in situ sensing of cancer biomarker flap endonuclease 1 (FEN1) and spatiotemporally modulating drug release. The gold nanostar-conjugated FEN1 substrate acts as spherical nucleic acid and induces a fluorescence signal upon a FEN1 stimulus for diagnosis. Guided by the nanoflare, external NIR light then triggers a controlled release of carried drugs at desired sites. This DNA nanosphere not only exhibits good stability, sensitivity, and specificity toward FEN1 assay but also serves as a precision theranostic agent for targeted and controlled drug delivery. Our study provides a reliable method for FEN1 imaging in vitro and in vivo and suggests a powerful strategy for precision medicine.

Omnidirectional stereo depth estimation based on spherical deep network

Omnidirectional depth estimation is an emerging research topic and has received significant attention in recent years. However, the existing methods were developed based on the theory of planar stereo matching; and introduce the nonlinear epipolar constraint and significant distortions of re-projections. In this paper, we propose a novel approach that use spherical CNNs and the epipolar constraint on sphere for omnidirectional depth estimation. We discuss the epipolar constraint for spherical stereo imaging and convert the nonlinear constraint on a planar projection to the linear constraint on a sphere. We then propose a Spherical Convolution Residual Network (SCRN) for omnidirectional depth estimation via the spherical linear epipolar constraint. The input equirectangular projection (ERP) images are sampled to spherical meshes and fed into SCRN to calculate spherical depth maps. For 2D visualization, we design a Planar Refinement Network (PRN) and adopt the cascade learning scheme to improve the accuracy of depth maps. This scheme reduces the errors caused by projection, interpolation, and the limitation of spherical representation. The experiment shows that our full scheme Cascade Spherical Depth Network (CSDNet) results in more accurate and detailed depth maps with lower errors, as compared to recent seminal works. Our approach yields the comparable performance to the other state-of-the-art works on the omnidirectional stereo datasets with less number of parameters. The effectiveness of the spherical network and the cascade learning scheme is validated, and the influence of spherical sampling density is also discussed.

DiLO: Direct light detection and ranging odometry based on spherical range images for autonomous driving

Over the last few years, autonomous vehicles have progressed very rapidly. The odometry technique that estimates displacement from consecutive sensor inputs is an essential technique for autonomous driving. In this article, we propose a fast, robust, and accurate odometry technique. The proposed technique is light detection and ranging (LiDAR)-based direct odometry, which uses a spherical range image (SRI) that projects a three-dimensional point cloud onto a two-dimensional spherical image plane. Direct odometry is developed in a vision-based method, and a fast execution speed can be expected. However, applying LiDAR data is difficult because of the sparsity. To solve this problem, we propose an SRI generation method and mathematical analysis, two key point sampling methods using SRI to increase precision and robustness, and a fast optimization method. The proposed technique was tested with the KITTI dataset and real environments. Evaluation results yielded a translation error of 0.69%, a rotation error of 0.0031°/m in the KITTI training dataset, and an execution time of 17 ms. The results demonstrated high precision comparable with state-of-the-art and remarkably higher speed than conventional techniques.

Applications of the Water-Dispersible L-Cysteine-Capped ZnS:Mn Nanocrystals as a Selective Photosensor and an Efficient Photocatalyst.

In this study, the ZnS:Mn nanocrystals (NCs) were prepared by capping the NC surface with a conventional amino acid, L-cysteine (Cys) molecules, at an acidic (pH 5) aqueous solution. The optical and physical characterizations of the ZnS:Mn-Cys-pH5 NCs were performed using various spectroscopic methods. For instance, the UV-visible and PL spectra of the ZnS:Mn-Cys-pH5 NCs showed broad peaks at 296 and 586 nm, respectively. The obtained HR-TEM image of the ZnS:Mn- Cys-pH5 NCs product showed spherical particle images with an average size of 6.15 nm in the solid state. In addition, measured surface charge of the colloidal ZnS:Mn-Cys-pH5 NCs using a zeta-PSA spectroscopy was -57.9 mV even at the acidic preparation condition. Therefore, the ZnS:Mn-Cys-pH5 NCs were applied as a photosensor to detect specific transition metal cations. As a result, the ZnS:Mn-Cys-pH5 NCs showed exclusive luminescence quenching effect for Fe(II) ions, which suggested that the ZnS:Mn-Cys-pH5 NCs can be applied as a photo-chemical sensor for Fe2+ ion detection in a practical water sample. The sensing ion selectivity of the ZnS:Mn-Cys-pH5 NCs was completely different comparing to ZnS:Mn NCs surface capped with other amino acids at the same condition. In addition, the catalytic activity of the ZnS:Mn-Cys-pH5 NCs was studied in the degradation reaction of an organic dye (methylene blue) molecule under UV light irradiation.

ON SPHERICAL INDICATRICES AND THEIR SPHERICAL IMAGE OF NULL CURVES IN MINKOWSKI 3-SPACE

In this paper, we investigate the spherical images of null curves and null helixes in Minkowski 3-space. We provide the spherical indicatrices of null curves in Minkowski 3-space with their causal characteristics. We also show the conditions of spherical indicatrices of null curves to be a curve lying on pseudo-sphere in Minkowski 3-space. In addition, we give the properties of spherical indicatrices of null curves satisfying generalized helices and lying on pseudo-sphere in Minkowski 3-space.

Self-Calibration Spherical Video Stabilization Based on Gyroscope

With the development of handheld video capturing devices, video stabilization becomes increasingly important. The gyroscope-based video stabilization methods perform promising ability, since they can return more reliable three-dimensional (3D) camera rotation estimation, especially when there are many moving objects in scenes or there are serious motion blur or illumination changes. However, the gyroscope-based methods depend on the camera intrinsic parameters to execute video stabilization. Therefore, a self-calibrated spherical video stabilization method was proposed. It builds a virtual sphere, of which the spherical radius is calibrated automatically, and then projects each frame of the video to the sphere. Through the inverse rotation of the spherical image according to the rotation jitter component, the dependence on the camera intrinsic parameters is relaxed. The experimental results showed that the proposed method does not need to calibrate the camera and it can suppress the camera jitter by binding the gyroscope on the camera. Moreover, compared with other state-of-the-art methods, the proposed method can improve the peak signal-to-noise ratio, the structural similarity metric, the cropping ratio, the distortion score, and the stability score.

Estimation of forest canopy structure and understory light using spherical panorama images from smartphone photography

Abstract Accurate estimates of forest canopy structure are central for a wide range of ecological studies. Hemispherical photography (HP) is a popular tool to estimate canopy attributes. However, traditional HP methods require expensive equipment, are sensitive to exposure settings, and produce limited resolution which dramatically affects the accuracy of gap fraction estimates. As an alternative, hemispherical images can be extracted from spherical panoramas produced by many smartphone camera applications. I compared hemispherical photos captured with a digital single lens reflex camera and 180° lens to those extracted from smartphone spherical panoramas (SSP). The SSP HP method leverages built-in features of current generation smartphones to produce sharper images of higher resolution, resulting in more definition of fine canopy structure. Canopy openness and global site factor from SSP HP are highly correlated with traditional methods (R2 > 0.9), while leaf area index estimates are lower, especially in more closed canopies where traditional methods fail to capture fine gaps.

Sampling with probability proportional to prediction (3P sampling) using covariates derived from spherical images

Using a two-phase sampling approach with systematic selection of large samples of covariates followed by a sampling with probability proportional to prediction (3P sampling) process to subsample field measures of the parameters of interest can be an efficient design to sample larger forest areas. To assist in obtaining predictions for each sample plot consistently and rapidly, we propose using a 360° spherical camera. In this study, three covariates derived from spherical images were evaluated: (i) basal area (P[BA]); (ii) sum of squared heights per hectare (P[SHT]); and (iii) stem fraction (P[SF]). These covariates were used to estimate volume. Sample simulations showed no biases in volume estimates for any of the three covariates. Overall, P[SF] had the lowest standard error percentages across different simulated sample sizes (10% for five subsamples to 2.5% for 50 subsamples), even though it had the lowest correlations with field volume (correlation = 0.30–0.31). This may be a result of the relatively consistent stand conditions within the study site. Based on our results, standard errors of 5% were obtainable with measurement fractions of about 25% of the number of image-based predictions when using P[SF] or P[BA] and 75% when using P[SHT].

Gold nanoparticles synthesized from Pergulariadaemia leaves extract for Antibacterial, anticancer and UV protection

Here in present work we studied the antibacterial and anticancer activity of gold nanoparticles (AuNPs), which are prepared through eco-friendly method using chloroauric acid and Pergulariadaemia leaves extract. The formation of the AuNPs and its structural features were fully examined by UV-Vis, SEM, HR-TEM and XRD analysis. The prepared AuNPs exhibited very high intense surface plasmon resonance (SPR) band in between 520 and 551 nm. SEM images showed AuNPs as spherical like morphology and HR-TEM images reveals the well-distributed AuNPs with average size of 30 nm. Further it was subjected to study antibacterial activity with various bacterial strains. The AuNPs coated cotton fabric has shown significant improvement in antibacterial activity against these strains. AuNPs coated cotton fabric display a superior UV-protection efficiency and it also exhibited finite anticancer response against HepG2 cell line.

Photon spheres and spherical accretion image of a hairy black hole

In this paper, we first consider null geodesics of a class of charged, spherical and asymptotically flat hairy black holes in an Einstein-Maxwell-scalar theory with a non-minimal coupling for the scalar and electromagnetic fields. Remarkably, we show that there are two unstable circular orbits for a photon in a certain parameter regime, corresponding to two unstable photon spheres of different sizes outside the event horizon. To illustrate the optical appearance of photon spheres, we then consider a simple spherical model of optically thin accretion on the hairy black hole, and obtain the accretion image seen by a distant observer. In the single photon sphere case, only one bright ring appears in the image, and is identified as the edge of the black hole shadow. Whereas in the case with two photon spheres, there can be two concentric bright rings of different radii in the image, and the smaller one serves as the boundary of the shadow, whose radius goes to zero at the critical charge.

THE RELIABILITY ASSESSMENT OF THE TLS REGISTRATION METHODS – THE CASE STUDY OF THE ROYAL CASTLE IN WARSAW

Abstract. Modern measurement technologies are commonly applied to monitor and preserve the cultural heritage as it is an integral part of modern societies. The Terrestrial Laser Scanning (TLS) method is one of the common technologies investigated by the researchers for accurate data acquisition and processing required for architectural documentation. In recent years, many methods were developed for TLS data registration to improve the processing time and accuracy of the bundle adjustment. The aim of this research is to compare the existing TLS target-based registration methods and compare them with the proposed novel method based on the reliability assessment- the robustness analysis. The novel feature-based approach also includes 2D detectors, which were applied to the TLS data converted into spherical images. Measurements were carried out at the Royal Castle in Warsaw using TLS Z+F 5006H and total station Leica TCRP1202. The collected data was analysed using existing software Z+F LaserControl, LupoScan and developed the application to perform 2D + 1H / 3D registration. The main results demonstrated that the proposed method for TLS registration removed the outliers that could not be eliminated by the deviation analysis on control and check points. The accuracy of TLS registration increased with a RMSE difference between 0.1 mm and 3.7 mm in comparison to existing methods. Furthermore, the accuracy of the results from 2D detectors was improved with relative orientation RMSE ≤ 2.1 mm and equivalent for control and check points for X, Y, and Z coordinates in comparison to target-based registration.

ULSD: Unified line segment detection across pinhole, fisheye, and spherical cameras

Image line segment detection is a fundamental problem in computer vision and remote sensing. Although numerous state-of-the-art methods have shown great performance for straight line segment detection, line segment detection for distorted images without undistortion is still a challenging problem. Besides, there is a lack of a unified line segment detection framework for both distorted and undistorted images. To address these two problems, we propose a novel learning-based Unified Line Segment Detection method (i.e., ULSD) for distorted and undistorted images in this paper. Specifically, we first propose a novel equipartition point-based Bezier curve representation to model arbitrary distorted line segments. Then the line segment detection is tackled by equipartition point regression with an end-to-end trainable neural network. Consequently, the proposed ULSD is independent of camera distortion parameters and does not need any undistortion preprocessing. In the experiments, the proposed method is firstly evaluated on the pinhole, fisheye, and spherical image datasets, respectively, as well as trained and tested on the mixed dataset with differently distorted images. The experimental results on each distortion model show that the proposed ULSD is more competitive than the state-of-the-art methods for both accuracy and efficiency, especially for the results of the unified model trained on the mixed datasets, thus demonstrating the effectiveness and generality of the proposed ULSD to real-world scenarios. The source code and datasets are available at https://github.com/lh9171338/ULSD-ISPRS.

Preparation and application of chiral silica gel spheres based on L-glutamic

无机介孔硅球因其具有足够的机械强度、热稳定性,以及适应多种流动相的优点,成为高效液相色谱(HPLC)柱填料中使用最广泛和最重要的材料。但在此研究领域中,并未见球形的全无机手性硅胶用作HPLC手性固定相。该文以无机球形介孔硅胶作为研究对象,通过堆砌硅珠法,以硅溶胶为原料,L-谷氨酸(L-Glu)为手性源,在手性环境中制造出脲醛树脂与胶体二氧化硅混合的小球,在550 ℃高温下煅烧除去树脂部分,制备基于L-Glu的无机介孔硅胶球。通过元素分析、红外光谱、扫描电镜、透射电镜和氮气吸附等表征证明这是一种具有规则球形的手性硅胶球,其手性来源于硅胶球自身的骨架和孔结构。将L-Glu手性硅胶球作为固定相制备了HPLC色谱柱,以正己烷-异丙醇(9∶1, v/v)作为流动相,流速为0.1 mL/min,考察了该手性柱对一系列外消旋化合物的拆分性能。实验表明,该手性柱拆分了15种外消旋化合物,其中特罗格尔碱、吡喹酮、3-苄氧基-1,2-丙二醇、1,2-环氧己烷、3-羟基-2-丁酮、2-甲基四氢呋喃-3-酮、异丙基缩水甘油醚达到基线分离;还分离了10种苯系位置异构体,o,m,p-氨基苯酚、o,p-氯苯酚、o,m,p-碘苯胺、o,m,p-甲苯胺、o,m,p-二硝基苯、o,m,p-氯苯胺、o,m,p-硝基苯酚、o,m,p-溴苯胺达到基线分离。实验表明,L-Glu手性硅胶球在手性分离方面具有良好的可行性,与普通硅胶相比不需要进一步修饰就可以有较好的手性分离效果,是一种低成本、制备便捷的手性无机硅胶固定相。

A High-Resolution Microfluidic LAPS Imaging System for 3D Cell Metabolism Monitoring

A High-Resolution Microfluidic LAPS Imaging System for 3D Cell Metabolism Monitoring

Characterizations of Tzitzeica curves using Bishop frames

In this study, the conditions of a regular curve to be Tzitzeica curve according to Type‐1 and Type‐2 Bishop frames in Euclidean 3‐space are formulated. Also, the conditions for each Bishop spherical images of a regular curve to be Tzitzeica curves are obtained. Moreover, comprehensive investigations are given for a curve to be a Tzitzeica curve in the special cases of the curvatures of this curve. Also, the curves lying in different planes spanned by different elements of Type‐1 and Type‐2 Bishop frames are considered, and the conditions of these curves to be Tzitzeica curves are expressed in these cases.

Spherical Image Generation from a Single Image by Considering Scene Symmetry

Spherical images taken in all directions (360 degrees by 180 degrees) allow the full surroundings of a subject to be represented, providing an immersive experience to viewers. Generating a spherical image from a single normal-field-of-view (NFOV) image is convenient and expands the usage scenarios considerably without relying on a specific panoramic camera or images taken from multiple directions; however, achieving such images remains a challenging and unresolved problem. The primary challenge is controlling the high degree of freedom involved in generating a wide area that includes all directions of the desired spherical image. We focus on scene symmetry, which is a basic property of the global structure of spherical images, such as rotational symmetry, plane symmetry, and asymmetry. We propose a method for generating a spherical image from a single NFOV image and controlling the degree of freedom of the generated regions using the scene symmetry. To estimate and control the scene symmetry using both a circular shift and flip of the latent image features, we incorporate the intensity of the symmetry as a latent variable into conditional variational autoencoders. Our experiments show that the proposed method can generate various plausible spherical images controlled from symmetric to asymmetric, and can reduce the reconstruction errors of the generated images based on the estimated symmetry.

Biomass estimates derived from sector subsampling of 360° spherical images

Abstract Efficient subsampling designs reduce forest inventory costs by focusing sampling efforts on more variable forest attributes. Sector subsampling is an efficient and accurate alternative to big basal area factor (big BAF) sampling to estimate the mean basal area to biomass ratio. In this study, we apply sector subsampling of spherical images to estimate aboveground biomass and compare our image-based estimates with field data collected from three early spacing trials on western Newfoundland Island in eastern Canada. The results show that sector subsampling of spherical images produced increased sampling errors of 0.3–3.4 per cent with only about 60 trees measured across 30 spherical images compared with about 4000 trees measured in the field. Photo-derived basal area was underestimated because of occluded trees; however, we implemented an additional level of subsampling, collecting field-based basal area counts, to correct for bias due to occluded trees. We applied Bruce’s formula for standard error estimation to our three-level hierarchical subsampling scheme and showed that Bruce’s formula is generalizable to any dimension of hierarchical subsampling. Spherical images are easily and quickly captured in the field using a consumer-grade 360° camera and sector subsampling, including all individual tree measurements, were obtained using a custom-developed python software package. The system is an efficient and accurate photo-based alternative to field-based big BAF subsampling.

A broadband spherical prism imaging spectrometer based on a single integrated module

The application range of hyperspectral imaging is subject to the operational system platform especially relies on the core imaging spectrometer. With a rising practical requirement of extensive remote sensing recently, the traditional method of two or multiple separate imaging submodules combined has obviously brought inevitable shortages in certain cases such as mineral detection or environmental monitoring, etc. Not only is the whole imaging system somewhat so large in physical size and so high in weight that it has an objective influence on convenience as well as flexibility in actual operation, but also each independent instrument has unique optical parameters and assembling matrices after fabrication and alignment which is against the image consistency. Instead of common image correction and data processing, the essential solution is to set up a broadband integrative system platform. This paper introduces a new prototype of imaging spectrometer in the visible and near-infrared (VNIR) to short-wave infrared (SWIR) region. Different from most existing research-based and commercial VNIR to SWIR imaging spectrometers, it is designed as broadband integration of a single core module. The main optical system consists of a collimating mirror, a central dispersive spherical prism, a converging mirror and two plane mirrors on the sides, which is similar to the normal convex grating spectrometer of three-concentric-mirror (Offner) configuration. The imaging spectrometer has relatively high imaging quality and satisfactory instantaneous field of view (IFOV) with a fairly compact internal structure benefiting from the integrated design and conscientious fabrication. The approach not only avoids extra expense and alignment complexities of multiple spectrometers but also enhances radiometric stability and reduces stray light and polarization effects. Relative performance tests are performed in various specific environment and validating imaging experiments are represented on schedule to demonstrate the expectant effectiveness of the whole system.

Quadrotor going through a window and landing: An image-based visual servo control approach

This paper considers the problem of controlling a quadrotor to go through a window and land on a planar target, the landing pad, using an Image-Based Visual Servo (IBVS) controller that relies on sensing information from two on-board cameras and an IMU. The maneuver is divided into two stages: crossing the window and landing on the pad. For the first stage, a control law is proposed that guarantees that the vehicle will not collide with the wall containing the window and will go through the window with non-zero velocity along the direction orthogonal to the window, keeping at all times a safety distance with respect to the window edges. For the landing stage, the proposed control law ensures that the vehicle achieves a smooth touchdown, keeping at all time a positive height above the plane containing the landing pad. For control purposes, the centroid vectors provided by the combination of the spherical image measurements of a collection of landmarks (corners) for both the window and the landing pad are used as position measurement. The translational optical flow relative to the wall, window edges, and landing plane is used as velocity cue. To achieve the proposed objective, no direct measurements nor explicit estimate of position or velocity are required. Simulation and experimental results are provided to illustrate the performance of the presented controller.