Entire 3D Space Research Articles

Efficient second-order accurate scheme for fluid–surfactant systems on curved surfaces with unconditional energy stability

Accurately simulating the interplay between fluids and surfactants is a challenge, especially when ensuring both mass conservation and guaranteed energy stability. This study proposes a highly accurate numerical scheme for the water–oil–surfactant system coupled with the Navier–Stokes equation. We use the second-order accurate discrete operators on triangular grids representing these surfaces. We use the Crank–Nicolson method to achieve the second-order temporal accuracy. To handle high-order nonlinearities, we employ the consistency-enhanced Scalar Auxiliary Variable method. Additionally, the projection method tackles the Navier–Stokes equations. These techniques guarantee the unconditional stability. Consequently, larger time steps are permissible. Our method achieves the high accuracy with lower computational cost. This efficiency stems from solely utilizing surface information, eliminating the need for calculations across the entire 3D space. The proposed scheme’s accuracy, stability, and robustness can be confirmed through various numerical experiments.

Context-based local-global fusion network for 3D point cloud classification and segmentation

3D point clouds have gained much research attention because of their ability to represent the spatial information of real-world environments in a detailed manner. Despite recent progress in point cloud processing with deep neural networks, most of them either implement sophisticated local feature aggregation methods or imitate 2D convolution operations in the range of K nearest neighbors with limited local context information. These methods may struggle to distinguish between similar geometric shapes within the local region of K nearest neighbors, such as doors and walls. To address this issue, we propose a novel local–global fusion network that captures the diverse local geometric shapes with global structure information. The proposed local–global fusion network comprises two main modules. Firstly, we have developed an effective approach for local context learning using incremental dilated KNN (IDKNN) as the neighbor selecting mechanism to enlarge the receptive field and incorporate more reliable points for local geometric shape learning. Secondly, a three-direction region-wise spatial attention (TRSA) algorithm has been developed to explore the global contextual dependencies. For global context learning, we first split the entire 3D space into regions with equal numbers of points, and, then, intra-region context features are extracted to learn the inter-region relations from three orthogonal directions, taking global structural knowledge into account. By fusing the local context information and global contextual dependencies, we establish a Local-Global Fusion Network, end-to-end framework, called LGFNet. Extensive experimental results on several benchmark datasets clearly demonstrate our approach can achieve state-of-the-art (SOTA) performance on point cloud classification, part segmentation, and indoor semantic segmentation. In addition, TRSA and IKDNN can be easily used in a plug-and-play fashion with various existing SOTA networks to substantially improve their performance. Our code is available at https://github.com/jasonwjw/IDKNN

Counting and Localization of Multiple Unknown Harmonic Sound Sources in Entire 3D Space Using Just Five Microphones

Counting and localization of multiple sound sources in an unknown environment has many applications, namely fault diagnosis of complex machineries, hearing aids' development, and localization of enemy vehicles in defense. However, multiple sound source localization is extremely challenging because it requires numerous microphones, which increases the cost, computational time, and installation difficulties. Here, we present a new method to count the number of stationary harmonic sound sources and localize them in a free-field environment using a novel oblique square pyramid shaped array of only 5 microphones. We find FFT peaks of microphone signals and compare the ratio of the magnitude of the most dominant peak with remaining peaks' one-by-one. If these ratios are below 25 dB difference, they are considered as sound source and counted. A new time delay and intensity ratio computation is applied to the segregated source signals to calculate exact coordinates of each source. Simulation studies of four concurrent sources show that our method predicts all sources' coordinates at every octant location with mean error of 3.4%, and less than 5% error beyond 20 dB Signal-to-Noise ratio. Mean computational time is 0.92 second. Therefore, our method is low-cost, quicker, more accurate and more reliable than existing techniques.

Metasurface‐Based Structured Light Sensing Without Triangulation

AbstractStructured light (SL) sensing technology, based on the triangulation principle, is widely employed for depth perception in various applications such as face recognition, human‐computer interaction, machine vision, and more. In this approach, the baseline length, which refers to the distance between the projection device and the camera, is a critical parameter that affects depth measurement and system miniaturization. Recently, metasurfaces have emerged as promising devices for constructing compact optoelectronic systems due to their excellent performance in wavefront modulation of light and ultra‐thin characteristics. In this study, a metasurface‐based monocular SL depth detection scheme is proposed that incorporates a specially designed 3D holographic projection. Under this projected light field, the entire 3D space is labeled, and depth information can be obtained without considering the baseline length, which can further reduce the volume of SL systems. Additionally, a template‐matching algorithm based on correlation coefficient analysis is developed and experimentally demonstrates its feasibility by precisely positioning objects. It is believed that this work opens up a new perspective for compact, lightweight, and flexible design of SL sensing systems, and has a promising future in quantitative detection, automatic location, and industrial measurement.

Sound source localization of harmonic sources in entire 3D space using just 5 acoustic signals

Sound Source Localization (SSL) has numerous applications namely machinery noise control, machinery fault localization, localization of explosives and weaponry in defense, development of hearing aids and robot’s auditory system. Beamforming and holographic SSL methods require numerous microphones and measurements for predicting source location; hence are highly expensive and time consuming. The simpler alternatives require less microphones; but are inaccurate, require high SNR, and have space of non-convergence where source cannot be uniquely localized. There is also a lack of method to localize pure harmonic sources. This paper proposes a method that addresses these limitations by accurately and quickly identifying the exact location of a harmonic sound source in the complete 3D space in acoustic free-field using just five acoustic signals. The novelties of this method are: new array design, spatially averaged Time Delay Estimation (TDE), TDE-ER (Energy Ratio) based localization, ER to remove mirror points, spectral de-noising, and solution of non-convergence. The method is rigorously tested through numerous simulations and real-life free-field experiments. A performance comparison shows that proposed method is more accurate (6.7% error) compared with the existing 3D SSL technique (11.7% error). Overall, it accurately identifies the coordinates of dominant sound source with 9.17% mean error, in presence of inherent sensor noise (14 dB SNR onwards) and background noise (8 dB SNR onwards) in complete 3D space. Interestingly, the sound source location, and sound source frequency is found to effect the consistency of TDE-based SSL methods. The presented work paves way for further advancement in 3D SSL.

Acquisition and Visualization of Micro-Vibration of a Sound Wave in 3D Space

The acquisition of micro-vibrations is important for analyzing machinery. In the present study, we propose a method for measuring and visualizing the three-dimensional (3D) displacements of such micro-vibrations, especially in the case of sound waves propagating through space. The proposed method uses the speckle patterns of coherent light to measure the minute displacements. Speckle patterns are useful for detecting extremely small displacements owing to their sensitivity to the pose of the object. However, it is impossible to measure the displacement at each position because the pattern changes nonlinearly with respect to large depth changes. Therefore, a method of nonlinear low-dimensional embedding of the speckle pattern is proposed to analyze the displacements and extended to measure micro-displacements in a 3D space. We divided the 3D space into multiple slices and synchronously captured each speckle pattern. The displacements in the entire 3D space were simultaneously recovered by optimizing the embedded vectors, which were consistent in a 3D lattice. The propagation of sound waves in the 3D space was visualized using the volume-rendering technique. The experiments confirmed that the proposed method correctly measured the displacements by comparing them with the ground truth captured by microphones. We also visualized the wavefront of the sound wave propagating through space.

Accurate diffraction field calculation method based on L1-norm minimization from three-dimensional objects.

Calculation of a three-dimensional (3D) diffraction field from arbitrarily distributed field samples over 3D space is an important problem in holographic 3D television systems. Straightforward superposition of diffracted fields from the samples may not provide accurate calculation of the diffraction field because of the possible mutual couplings between those samples. We define an inverse problem to overcome that deviation caused by mutual couplings. First, the diffraction field on a reference plane is estimated accurately from the known field values at the sampling points. Then, the diffraction field over the entire space can be calculated from the field on the reference plane. Sparse representation of the diffraction field on the reference plane may provide a suitable framework in terms of L1-norm minimization. Once the diffraction field over the reference plane is obtained, the harmonics that form the diffraction field can be calculated. After that, the field over the entire 3D space can be found by using those harmonics. In this work, we proposed a method based on the SPGL1 algorithm that solves the inverse problem of accurate calculation of the diffraction field on the reference plane by using fewer samples in calculation compared to the methods based on L2-norm minimization. Furthermore, the proposed method requires less memory allocation as well.

GlyphLens: View-Dependent Occlusion Management in the Interactive Glyph Visualization.

Glyph as a powerful multivariate visualization technique is used to visualize data through its visual channels. To visualize 3D volumetric dataset, glyphs are usually placed on 2D surface, such as the slicing plane or the feature surface, to avoid occluding each other. However, the 3D spatial structure of some features may be missing. On the other hand, placing large number of glyphs over the entire 3D space results in occlusion and visual clutter that make the visualization ineffective. To avoid the occlusion, we propose a view-dependent interactive 3D lens that removes the occluding glyphs by pulling the glyphs aside through the animation. We provide two space deformation models and two lens shape models to displace the glyphs based on their spatial distributions. After the displacement, the glyphs around the user-interested region are still visible as the context information, and their spatial structures are preserved. Besides, we attenuate the brightness of the glyphs inside the lens based on their depths to provide more depth cue. Furthermore, we developed an interactive glyph visualization system to explore different glyph-based visualization applications. In the system, we provide a few lens utilities that allows users to pick a glyph or a feature and look at it from different view directions. We compare different display/interaction techniques to visualize/manipulate our lens and glyphs.

Fitting boxes to Manhattan scenes using linear integer programming

ABSTRACTWe propose an approach for automatic generation of building models by assembling a set of boxes using a Manhattan-world assumption. The method first aligns the point cloud with a per-building local coordinate system, and then fits axis-aligned planes to the point cloud through an iterative regularization process. The refined planes partition the space of the data into a series of compact cubic cells (candidate boxes) spanning the entire 3D space of the input data. We then choose to approximate the target building by the assembly of a subset of these candidate boxes using a binary linear programming formulation. The objective function is designed to maximize the point cloud coverage and the compactness of the final model. Finally, all selected boxes are merged into a lightweight polygonal mesh model, which is suitable for interactive visualization of large scale urban scenes. Experimental results and a comparison with state-of-the-art methods demonstrate the effectiveness of the proposed framework.

Volumetric view planning for 3D reconstruction with multiple manipulators

Purpose– This paper aims to propose a new view planning method which can be used to calculate the next-best-view (NBV) for multiple manipulators simultaneously and build an automated three-dimensional (3D) object reconstruction system, which is based on the proposed method and can adapt to various industrial applications.Design/methodology/approach– The entire 3D space is encoded with octree, which marks the voxels with different tags. A set of candidate viewpoints is generated, filtered and evaluated. The viewpoint with the highest score is selected as the NBV.Findings– The proposed method is able to make the multiple manipulators, equipped with “eye-in-hand” RGB-D sensors, work together to accelerate the object reconstruction process.Originality/value– Compared to the existed approaches, the proposed method in this paper is fast, computationally efficient, has low memory cost and can be used in actual industrial productions where the multiple different manipulators exist. And, more notably, a new algorithm is designed to speed up the generation and filtration of the candidate viewpoints, which can guarantee both speed and quality.

Bioimpedance monitoring of 3D cell culturing—Complementary electrode configurations for enhanced spatial sensitivity

A bioimpedance platform is presented as a promising tool for non-invasive real-time monitoring of the entire process of three-dimensional (3D) cell culturing in a hydrogel scaffold. In this study, the dynamics involved in the whole process of 3D cell culturing, starting from polymerisation of a bare 3D gelatin scaffold, to human mesenchymal stem cell (MSC) encapsulation and proliferation, was monitored over time. The platform consists of a large rectangular culture chamber with four embedded vertical gold plate electrodes that were exploited in two- and three terminal (2T and 3T) measurement configurations. By switching between the different combinations of electrode couples, it was possible to generate a multiplexing-like approach, which allowed for collecting spatially distributed information within the 3D space. Computational finite element (FE) analysis and electrochemical impedance spectroscopic (EIS) characterisation were used to determine the configurations’ sensitivity field localisation. The 2T setup gives insight into the interfacial phenomena at both electrode surfaces and covers the central part of the 3D cell culture volume, while the four 3T modes provide focus on the dynamics at the corners of the 3D culture chamber. By combining a number of electrode configurations, complementary spatially distributed information on a large 3D cell culture can be obtained with maximised sensitivity in the entire 3D space. The experimental results show that cell proliferation can be monitored within the tested biomimetic environment, paving the way to further developments in bioimpedance tracking of 3D cell cultures and tissue engineering.

SU-E-T-69: Cloud-Based Monte Carlo Patient-Specific Quality Assurance (QA) Method for Volumetric Modulated Arc Therapy (VMAT)

Purpose: Patient-specific QA for VMAT is incapable of providing full 3D dosimetric information and is labor intensive in the case of severe heterogeneities or small-aperture beams. A cloud-based Monte Carlo dose reconstruction method described here can perform the evaluation in entire 3D space and rapidly reveal the source of discrepancies between measured and planned dose. Methods: This QA technique consists of two integral parts: measurement using a phantom containing array of dosimeters, and a cloud-based voxel Monte Carlo algorithm (cVMC). After a VMAT plan was approved by a physician, a dose verification plan was created and delivered to the phantom using our Varian Trilogy or TrueBeam system. Actual delivery parameters (i.e., dose fraction, gantry angle, and MLC at control points) were extracted from Dynalog or trajectory files. Based on the delivery parameters, the 3D dose distribution in the phantom containing detector were recomputed using Eclipse dose calculation algorithms (AAA and AXB) and cVMC. Comparison and Gamma analysis is then conducted to evaluate the agreement between measured, recomputed, and planned dose distributions. To test the robustness of this method, we examined several representative VMAT treatments. Results: (1) The accuracy of cVMC dose calculation was validated via comparative studies. For cases that succeeded the patient specific QAs using commercial dosimetry systems such as Delta- 4, MAPCheck, and PTW Seven29 array, agreement between cVMC-recomputed, Eclipse-planned and measured doses was obtained with >90% of the points satisfying the 3%-and-3mm gamma index criteria. (2) The cVMC method incorporating Dynalog files was effective to reveal the root causes of the dosimetric discrepancies between Eclipse-planned and measured doses and provide a basis for solutions. Conclusion: The proposed method offers a highly robust and streamlined patient specific QA tool and provides a feasible solution for the rapidly increasing use of VMAT treatments in the clinic.

3D human posture segmentation by spectral clustering with surface normal constraint

In this paper, we propose a new algorithm for partitioning human posture represented by 3D point clouds sampled from the surface of human body. The algorithm is formed as a constrained extension of the recently developed segmentation method, spectral clustering (SC). Two folds of merits are offered by the algorithm: (1) as a nonlinear method, it is able to deal with the situation that data (point cloud) are sampled from a manifold (the surface of human body) rather than the embedded entire 3D space; (2) by using constraints, it facilitates the integration of multiple similarities for human posture partitioning, and it also helps to reduce the limitations of spectral clustering. We show that the constrained spectral clustering (CSC) still can be solved by generalized eigen-decomposition. Experimental results confirm the effectiveness of the proposed algorithm.

MAS NMR Structure of a Microcrystalline Cd-Bacteriochlorophyll d Analogue

Solid-state NMR is an emerging method to obtain structural information in molecular biology and nanotechnology for systems that are inaccessible to solution NMR or diffraction methods. While solution NMR generally converges upon families of structures in a bottom-up approach, solid NMR structure determination will have to take into account the top-down constraints that follow from the additional requirement that the entire 3D space must be packed in an orderly fashion. We used MAS NMR together with molecular modeling calculations in steps to establish a detailed model of the local crystal structure of an aggregate of uniformly 13C- and 15N-labeled Cd-chlorophyllide d, a model for the chlorosomal antennae. In this way we converge upon a space group P21 with a = 14.3 A, b = 27.3 A, c = 6.4 A, beta = 147.2 degrees and Z = 2.

Electron cryomicroscopy structure of N-ethyl maleimide sensitive factor at 11 A resolution.

N-ethyl maleimide sensitive factor (NSF) belongs to the AAA family of ATPases and is involved in a number of cellular functions, including vesicle fusion and trafficking of membrane proteins. We present the three-dimensional structure of the hydrolysis mutant E329Q of NSF complexed with an ATP-ADP mixture at 11 A resolution by electron cryomicroscopy and single-particle averaging of NSF.alpha-SNAP.SNARE complexes. The NSF domains D1 and D2 form hexameric rings that are arranged in a double-layered barrel. Our structure is more consistent with an antiparallel orientation of the two rings rather than a parallel one. The crystal structure of the D2 domain of NSF was docked into the EM density map and shows good agreement, including details at the secondary structural level. Six protrusions corresponding to the N domain of NSF (NSF-N) emerge from the sides of the D1 domain ring. The density corresponding to alpha-SNAP and SNAREs is located on the 6-fold axis of the structure, near the NSF-N domains. The density of the N domain is weak, suggesting conformational variability in this part of NSF.

A survey of 3D texturing

Texturing is indispensable for the realistic rendering since it adds surface details that are usually too complex to be modeled directly. Conventional 2D texture mapping remains the most usual approach to texturing, in particular for real-time applications. However, there are some major drawbacks inherent to this approach: the distortion and the discontinuity of textures as well as the lack of the “third” dimension information (geometric effects like roughcast cannot be rendered). 3D texturing has been introduced to computer graphics to resolve these problems. There are two types of 3D texturing: solid texturing that consists of defining color variations through the entire 3D space instead of the 2D one and geometric texturing that consists of adding a “real” third dimension information to surfaces in the form of “real” apparent geometry. This paper presents a detailed survey of 3D texturing. Main principles, advantages, drawbacks and applications are presented. The crucial problem of 3D textures synthesis is studied with a particular attention to analytical methods as well as physical-based models that can provide interesting solutions to this problem.