Bounding Volume Research Articles

Nondestructive determination of common indicators of beef for freshness assessment using airflow-three dimensional (3D) machine vision technique and machine learning

Assessment of beef freshness is critical to ensure a safe and sustainable beef supply chain. This work aims to investigate the feasibility of the viscoelasticity of beef to evaluate its freshness using the airflow-3D machine vision technique and machine learning models. The 3D camera was continuously used to acquire deformation images under the action of the airflow. The obtained images were preprocessed using region of interest ( ROI ) segmentation, filtering denoising, and down-sampling. And then the depth and volume of processed images were obtained by the Oriented Bounding Box ( OBB ) algorithm and volume algorithms, separately. Two four-element viscoelastic models were established to fit depth and volume respectively for obtaining viscoelastic characteristics. Finally, regression models were built and compared using viscoelastic characteristics to determine the optimum prediction models and methods for two freshness indicators. The backpropagation neural network ( BPNN ) and SVR based on selected features were the best prediction models for pH and total volatile basic nitrogen ( TVB-N ) content evaluation in beef, and the correlation coefficients ( R c and R p ) of the calibration set and prediction set were 0.7636, 0.9036, and 0.7669, 0.8388, respectively. • A test electronic instrument based on airflow-3D machine vision was independently developed. • The depth and volume of spatial deformation were quantified by algorithms of point cloud image quantization. • Two four-element viscoelastic models of the creep recovery phase were established to extract viscoelastic characteristics. • Machine learning models for simultaneously predicting two common freshness indicators were built. • The prediction effects of different viscoelastic feature fusions and different models were compared.

LBVH 순회를 이용한 거대 도체 구조의 레이다 단면적 분석

In this study, the radar cross-section (RCS) of a large structure is analyzed using the linear bounding volume hierarchy (LBVH), which is a representative acceleration algorithm of the ray-tracing technique. A ray-tracing technique, which is a high-frequency method, is used to analyze the electromagnetic properties of large structures, and bounding volume hierarchy (BVH), a binary tree structure, is applied to reduce the intersection search time. The improvement in the calculation speed is quantitatively analyzed by dividing an arbitrary scatterer into several triangles. The calculation results are compared with those of multilevel fast multipole method (MLFMM) and ray-launching geometrical optics (RL-GO) using the Feko commercial software to verify the accuracy. The proposed technique can be utilized for the efficient RCS calculations of large structures.

Near Lossless Compression for 3D Radiological Images Using Optimal Multilinear Singular Value Decomposition (3D-VOI-OMLSVD).

Storage and transmission of high-compression 3D radiological images that create high-quality reconstruction upon decompression are critical necessities for effective and efficient teleradiology. To cater to this need, we propose a near lossless 3D image volume compression method based on optimal multilinear singular value decomposition called “3D-VOI-OMLSVD.” The proposed strategy first eliminates any blank 2D image slices from the 3D image volume and uses the selective bounding volume (SBV) to identify and extract the volume of Interest (VOI). Following this, the VOI is decomposed with an optimal multilinear singular value decomposition (OMLSVD) to obtain the corresponding core tensor, factor matrices, and singular values that are compressed with adaptive binary range coder (ABRC), integrated as an entropy encoder. The compressed file can be transferred or transmitted and then decompressed in order to reconstruct the original image. The resultant decompressed VOI is acquired by reversing the above process and then fusing it with the background, using the bound volume coordinates associated with the compressed 3D image. The proposed method performance was tested on a variety of 3D radiological images with different imaging modalities and dimensions using quantitative evaluation metrics such as the compression rate (CR), bit rate (BR), peak signal to noise ratio (PSNR), and structural similarity index (SSIM). Furthermore, we also investigate the impact of VOI extraction on the model performance, before comparing it with two popular compression methods, namely JPEG and JPEG2000. Our proposed method, 3D-VOI-OMLSVD, displayed a high CR value, with a maximum of 37.31, and a low BR, with the lowest reported to be 0.21. The SSIM score was consistently high, with an average performance of 0.9868, while using < 1 second for decoding the image. We observe that with VOI extraction, the compression rate increases manifold, and bit rate drops significantly, and thus reduces the encoding and decoding time to a great extent. Compared to JPEG and JPEG2000, our method consistently performs better in terms of higher CR and lower BR. The results indicate that the proposed compression methodology performs consistently to create high-quality image compressions, and overall gives a better outcome when compared against two state-of-the-art and widely used methods, JPEG and JPEG2000.

PLOC++

We propose a novel version of the GPU-oriented massively parallel locally-ordered clustering (PLOC) algorithm for constructing bounding volume hierarchies (BVHs). Our method focuses on removing the weaknesses of the original approach by simplifying and fusing different phases, while replacing most performance critical parts by novel and more efficient algorithms. This combination allows for outperforming the original approach by a factor of 1.9 - 2.3x.

Research on Building Space Model Method Based on Big Data Map Visual Design.

In order to explore the architectural space model of design, a visualization method based on big data map is proposed. Referring to the tile pyramid model, a multidimensional aggregation pyramid model (MAP) is proposed, which extends the 2D spatial hierarchical aggregation of tile pyramid to the multidimensional of time/space/attribute and supports the multidimensional hierarchical aggregation of time, space, and attribute. Then, taking spark cluster as the parallel preprocessing tool and HBase distributed database as the persistent storage of map model data, an open-source distributed visualization framework (MAP-Vis) is realized. Then, the BIM model is reconstructed, and a component instance hierarchical splitting strategy based on IFC structure tree is proposed to separate the digital and analog of the original IFC file. The reconstructed IFC model file is transformed into glTF format file, and the dual relationship mapping of geometric space and semantic attributes is completed in the transformation process. Finally, the visibility detection algorithm of BS-AB scene components based on the hierarchical bounding volume (BVH) structure is proposed to eliminate the visibility of building components. The experimental results show that BIMviews is slow to load the IFC file of the experimental object and obtain the model data, with an average of about 40 s, and the Caton is obvious. However, it only takes about 7 s to load glTF file into big data map visualization design by Three.js. It is verified again that glTF format is more suitable for BIM model data than IFC format. The visualization design, display, and interaction based on big data map are based on glTF format. It proves the effectiveness of big data map visualization.

Optimized 2D ball trees for shape layout applications

The interactive creation of 2D layouts involving irregular shapes such as text or images is typically carried out using a pointing device to select elements and drag them to new positions on a page. We propose augmenting layout interaction with two operations: overlap avoidance and grouping by distance. Since these are computationally expensive and may hinder the fluidity of the interaction, we examine several techniques that aim at implementing these features in an efficient manner. These techniques involve the approximation of 2D shapes by collections of balls (circles) which are then organized in ball trees, a bounding volume hierarchy. In particular, we discuss a new algorithm for approximating shapes with a reduced set of balls, as well as enhanced ball tree construction algorithms. These are used to implement algorithms to group shapes hierarchically by distance and to allow dragging with collision avoidance, in the context of a proof-of-concept web application for laying out shapes extracted from segmented images.

Quick Clusters: A GPU-Parallel Partitioning for Efficient Path Tracing of Unstructured Volumetric Grids.

We propose a simple yet effective method for clustering finite elements to improve preprocessing times and rendering performance of unstructured volumetric grids without requiring auxiliary connectivity data. Rather than building bounding volume hierarchies (BVHs) over individual elements, we sort elements along with a Hilbert curve and aggregate neighboring elements together, improving BVH memory consumption by over an order of magnitude. Then to further reduce memory consumption, we cluster the mesh on the fly into sub-meshes with smaller indices using a series of efficient parallel mesh re-indexing operations. These clusters are then passed to a highly optimized ray tracing API for point containment queries and ray-cluster intersection testing. Each cluster is assigned a maximum extinction value for adaptive sampling, which we rasterize into non-overlapping view-aligned bins allocated along the ray. These maximum extinction bins are then used to guide the placement of samples along the ray during visualization, reducing the number of samples required by multiple orders of magnitude (depending on the dataset), thereby improving overall visualization interactivity. Using our approach, we improve rendering performance over a competitive baseline on the NASA Mars Lander dataset from 6× (1 frame per second (fps) and 1.0 M rays per second (rps) up to now 6 fps and 12.4 M rps, now including volumetric shadows) while simultaneously reducing memory consumption by 3×(33 GB down to 11 GB) and avoiding any offline preprocessing steps, enabling high-quality interactive visualization on consumer graphics cards. Then by utilizing the full 48 GB of an RTX 8000, we improve the performance of Lander by 17 × (1 fps up to 17 fps, 1.0 M rps up to 35.6 M rps).

Learning to reconstruct botanical trees from single images

We introduce a novel method for reconstructing the 3D geometry of botanical trees from single photographs. Faithfully reconstructing a tree from single-view sensor data is a challenging and open problem because many possible 3D trees exist that fit the tree's shape observed from a single view. We address this challenge by defining a reconstruction pipeline based on three neural networks. The networks simultaneously mask out trees in input photographs, identify a tree's species, and obtain its 3D radial bounding volume - our novel 3D representation for botanical trees. Radial bounding volumes (RBV) are used to orchestrate a procedural model primed on learned parameters to grow a tree that matches the main branching structure and the overall shape of the captured tree. While the RBV allows us to faithfully reconstruct the main branching structure, we use the procedural model's morphological constraints to generate realistic branching for the tree crown. This constraints the number of solutions of tree models for a given photograph of a tree. We show that our method reconstructs various tree species even when the trees are captured in front of complex backgrounds. Moreover, although our neural networks have been trained on synthetic data with data augmentation, we show that our pipeline performs well for real tree photographs. We evaluate the reconstructed geometries with several metrics, including leaf area index and maximum radial tree distances.

An GPU-accelerated particle tracking method for Eulerian–Lagrangian simulations using hardware ray tracing cores

To address the high computational cost of particle tracking for realistic Eulerian–Lagrangian simulations, a novel efficient and robust particle tracking method (RT method) for unstructured meshes is presented. The method, for the first time, leverages both hardware ray tracing (RT) cores and GPU parallel computing technology to accelerate Eulerian–Lagrangian simulations. The method includes a hardware-accelerated hosting cell locator using bounding volume hierarchy tree (BVH) and a robust treatment of particle-wall interaction (multiple specular reflection) using an improved neighbor searching approach. The method is implemented in a GPU-accelerated open-source code, which is verified against a reference neighbor-searching particle-tracking method (NS method) and experimental observations. To evaluate the performance of our method, several numerical simulations of fluid-driven scalar transport problem are solved. Using a verification case, we show that the particle distribution simulated by our code is in a good agreement with an experimental observation. Tracking failures and stuck particles are not observed in any simulations. Benchmark results indicate that our RT method leads to a roughly 1.8−2.0× performance improvement compared to the reference NS method for large-scale simulations (millions of mesh cells and particles).

Smart system to generate the optimal authorized bounding volume

PurposeThe overall functioning of this system is based on two approaches: construction and supervision. The first is conducted entirely by the machine, and the second requires the intervention of the designer to collaborate with the machine. The morphological translation of urban rules is sometimes contradictory and may require additional external relevance to urban rules. Designer arbitration assists the artificial intelligence (AI) in accomplishing this task and solving the problem.Design/methodology/approachThis paper provides a method of computational design in generating the optimal authorized bounding volume which uses the best target values of morphological urban rules. It examines an intelligent system, adopting the multi-agent approach, which aims to control and increase urban densification by optimizing morphological urban rules. The process of the system is interactive and iterative. It allows collaboration and exchange between the machine and the designer. This paper is adopting and developing a new approach to resolve the distributed constraint optimization problem in generating the authorized bounding volume. The resolution is not limited to an automatic volume generation from urban rules, but also involves the production of multiple optimal-solutions conditioned both by urban constraints and relevance chosen by the designer. The overall functioning of this system is based on two approaches: construction and supervision. The first is conducted entirely by the machine and the second requires the intervention of the designer to collaborate with the machine. The morphological translation of urban rules is sometimes contradictory and may require additional external relevance to urban rules. Designer arbitration assists the AI in accomplishing this task and solving the problem. The human-computer collaboration is achieved at the appropriate time and relies on the degree of constraint satisfaction. This paper shows and analyses interactions with the machine during the building generation process. It presents different cases of application and discusses the relationship between relevance and constraints satisfaction. This topic can inform a chosen urban densification strategy by assisting a typology of the optimal authorized bounding volume.FindingsThe human-computer collaboration is achieved at the appropriate time and relies on the degree of constraint satisfaction with fitness function.Originality/valueThe resolution of the distributed constraint optimization problem is not limited to an automatic generation of urban rules, but involves also the production of multiple optimal ABV conditioned both by urban constraints as well as relevance, chosen by the designer.

A contact detection algorithm for triangle boundary in GPU-based DEM and its application in a large-scale landslide

Triangle boundaries are crucial geometric objects in the discrete element method (DEM). In this study, an improvement for the uniform grid method is proposed and implemented on the GPU. The improved algorithm includes the spatial discretization of triangles in which triangles are classified by their size and motion. The large and relative static triangles are separated into grid cells such that it relaxes the restriction of cell size in the uniform grid method. To verify the accuracy and efficiency of the algorithm, the improved grid method is compared with the normal uniform grid method and the linear bounding volume hierarchy (LBVH) method using a simulation of free-falling grains in a mixer. The results show that the improved grid method does significantly increase the simulation efficiency compared with the normal uniform grid method. Then, taking a large-scale landslide as an example, the improved grid method and the LBVH method are used to simulate the failure process of the landslide. The results indicate that the improved grid algorithm has higher efficiency for simulations of large-scale landslides than the LBVH method but at the cost of more memory usage.

A coupled lattice Boltzmann and Cosserat rod model method for three-dimensional two-way fluid–structure interactions

A numerical scheme to simulate three-dimensional two-way fluid–structure interaction (twFSI) problems of flows around a flexible fine structure is developed in this study. The partitioned approach is employed to separately calculate fluid flows and structure motions by the lattice Boltzmann method (LBM) and the geometrically exact Cosserat rod model (CRM), respectively. The fluid–structure interactions are calculated by the simple explicit coupling scheme combined with the contact detection algorithm and the fluid–structure interface reconstruction scheme. The contact detection algorithm utilizing the bounding volume hierarchy is adopted to reduce the computing time of data communication between the fluid and the structure solvers, while the fluid–structure interface reconstruction scheme utilizes the level set method to represent the moving fluid–structure interfaces. The proposed LBM–CRM–twFSI scheme is successfully validated in two experimental benchmarks of a single flexible structure deformation in a wind tunnel. The results confirm that the present scheme accurately calculates the equilibrium state and the time-dependent oscillatory motions of the structures exposed to airflows. The errors of the representative rod position between the experimental and numerical results for both benchmarks are within 5%. These validations confirm the practicability of the presently developed LBM–CRM–twFSI scheme for motions of flexible fine structures in fluid flows.

Grid-induced bounding volume hierarchy for ray tracing dynamic scenes

Grid-induced bounding volume hierarchy for ray tracing dynamic scenes

Saliency based human fall detection in smart home environments using posture recognition.

The implementation of people monitoring system is an evolving research theme. This paper introduces an elderly monitoring system that recognizes human posture from overlapping cameras for people fall detection in a smart home environment. In these environments, the zone of movement is limited. Our approach used this characteristic to recognize human posture fastly by proposing a region-wise modelling approach. It classifies persons pose in four groups: standing, crouching, sitting and lying on the floor. These postures are obtained by calculating an estimation of the human bounding volume. This volume is estimated by obtaining the height of the person and its surface that is in contact with the ground according to the foreground information of each camera. Using them, we distinguish each postures and differentiate lying on floor posture, which can be considered as the falling posture from other postures. The global multiview information of the scene is obtaining by using homographic projection. We test our proposed algorithm on multiple cameras based fall detection public dataset and the results prove the efficiency of our method.

On a hybrid lossless compression technique for three-dimensional medical images.

In the last two decades, incredible progress in various medical imaging modalities and sensing techniques have been made, leading to the proliferation of three‐dimensional (3D) imagery. Byproduct of such great progress is the production of huge volume of medical images and this big data place a burden on automatic image processing methods for diagnostic assistance processes. Moreover, large amount of medical imaging data needs to be transmitted with no loss of information for the purpose of telemedicine, remote diagnosis etc. In this work, we consider a hybrid lossless compression technique with object‐based features for three‐dimensional (3D) medical images. Our approach utilizes two phases as follows: first we determine the volume of interest (VOI) for a given 3D medical imagery using selective bounding volume (SBV) method, and second the obtained VOI is encoded using a hybrid lossless algorithm using Lembel‐Ziv‐Welch Coding (LZW) followed by arithmetic coding (L to A). Experimental results show that our proposed 3D medical image compression method is comparable with other existing standard lossless encoding methods such as Huffman Coding, Run Length Coding, LZW, and Arithmetic Coding and obtains superior results overall.

A Survey on Bounding Volume Hierarchies for Ray Tracing

AbstractRay tracing is an inherent part of photorealistic image synthesis algorithms. The problem of ray tracing is to find the nearest intersection with a given ray and scene. Although this geometric operation is relatively simple, in practice, we have to evaluate billions of such operations as the scene consists of millions of primitives, and the image synthesis algorithms require a high number of samples to provide a plausible result. Thus, scene primitives are commonly arranged in spatial data structures to accelerate the search. In the last two decades, the bounding volume hierarchy (BVH) has become the de facto standard acceleration data structure for ray tracing‐based rendering algorithms in offline and recently also in real‐time applications. In this report, we review the basic principles of bounding volume hierarchies as well as advanced state of the art methods with a focus on the construction and traversal. Furthermore, we discuss industrial frameworks, specialized hardware architectures, other applications of bounding volume hierarchies, best practices, and related open problems.

A Shader-Based Ray Tracing Engine

Recently, ray tracing techniques have been highly adopted to produce high quality images and animations. In this paper, we present our design and implementation of a real-time ray-traced rendering engine. We achieved real-time capability for triangle primitives, based on the ray tracing techniques on GPGPU (general-purpose graphics processing unit) compute shaders. To accelerate the ray tracing engine, we used a set of acceleration techniques, including bounding volume hierarchy, its roped representation, joint up-sampling, and bilateral filtering. Our current implementation shows remarkable speed-ups, with acceptable error values. Experimental results shows 2.5–13.6 times acceleration, and less than 3% error values for the 95% confidence range. Our next step will be enhancing bilateral filter behaviors.

Paralleling Collision Detection on Five-Axis Machining

With the rapid growth of the Fourth Industrial Revolution (or Industry 4.0), five-axis machining has played an important role nowadays. Due to the expensive cost of five-axis machining, how to solve the collision detection for five-axis machining in real-time is very critical. In this paper, we present a parallel method to detect collision for five-axis machining. Moreover, we apply the bounding volume hierarchy technique with two-level bounding volume represent the surface or solid of the object to reduce triangle meshes inside each axis of the five-axis machine tool, and then matching the operating range limit of the five-axis machine tool itself, delete the no colliding triangle mesh. Additionally, we also propose some optimization with loop unrolling and prefetching techniques to improve performance of collision detection. Our approach can reduce the execution time significantly by computing six separating axes in plan and eleven separating axis in non-plan between two triangle meshes based on the characteristic of GPUs (Graphics Processing Units) for program acceleration. Our proposed work consists of kinematic analysis and interpolation for axes to save the numerous collision detection for five-axis machining computations. In this experiment, the result shows that using the proposed approach above can achieve approximately 37.1 times speedup than that of CPU.

TOWARDS CAD-BASED GEOMETRY MODELLING WITH THE RANDOM RAY METHOD

The Advanced Random Ray Code (ARRC) is a high performance computing application capable of high-fidelity simulations of full core nuclear reactor models. ARRC leverages a recently developed stochastic method for neutron transport, known as The Random Ray Method (TRRM), which offers a variety of computational and numerical advantages as compared to existing methods. In particular, TRRM has been shown to be capable of efficient simulation of explicit three dimensional geometry representations without assumptions about axial homogeneity. To date, ARRC has utilized Constructive Solid Geometry (CSG) combined with a nested lattice geometry which works well for typical pressurized water reactors, but is not performant for the general case featuring arbitrary geometries. To facilitate simulation of arbitrarily complex geometries in ARRC efficiently, we propose performing transport directly on Computer-Aided Design (CAD) models of the geometry. In this study, we utilize the Direct-Accelerated Geometry Monte Carlo (DAGMC) toolkit which tracks particles on tessellated CAD geometries using a bounding volume hierarchy to accelerate the process, as a replacement for ARRC’s current lattice-based accelerations. Additionally, we present a method for automatically subdividing the large CAD regions in the DAGMC model into smaller mesh cells required by random ray to achieve high accuracy. We test the new DAGMC geometry implementation in ARRC on several test problems, including a 3D pincells, 3D assemblies, and an axial section of the Advanced Test Reactor. We show that DAGMC allows for simulation of complex geometries in ARRC that would otherwise not be possible using the traditional approach while maintaining solution accuracy.

Constructing K-d Tree on GPU through Treelet Restructuring

With every new generation of graphics processing units (GPUs), offloading ray-tracing algorithms to GPUs becomes more feasible. Software-hardware solutions for ray-tracing focus on implementing its basic components, such as building and traversing bounding volume hierarchies (BVH). However, global illumination algorithms, such as photon mapping method, depend on another kind of acceleration structure, namely k-d trees. In this work, we adapt state-ofthe-art GPU-based BVH-building algorithm of treelet restructuring to k-d trees. By evaluating the performance of the resulting k-d tree, we show that treelet optimisation heuristic suitable for BVHs of triangles is inadequate for k-d trees of points.