Intersection Tests Research Articles

Lipschitz-agnostic, efficient and accurate rendering of implicit surfaces

AbstractIn this paper, we propose an accurate and controllable rendering process for implicit surfaces with no or unknown analytic Lipschitz constants. Our process is built upon a ray-casting approach where we construct an adaptive Chebyshev proxy along each ray to perform an accurate intersection test via a robust and multi-stage searching method. By taking into account approximation errors and numerical conditions, our methods comprise several pre-conditioning and post-processing stages to improve the numerical accuracy, which potentially applied recursively. The intersection search is performed by evaluating a QR decomposition on the Chebyshev proxy function, which can be done in a numerically accurate way. Our process achieves comparable accuracy to other techniques that impose more constraints on the surface, e.g., knowledge of Lipschitz constants, and higher accuracy compared to approaches that impose similar constraints as our approach.

Geofencing Motion Planning for Unmanned Aerial Vehicles Using an Anticipatory Range Control Algorithm

This paper presents a range control approach for implementing hard geofencing for unmanned air vehicles (UAVs), and especially remotely piloted versions (RPVs), via a proposed anticipatory range calculator. The approach employs turning circle intersection tests that anticipate the fence perimeter on approach. This ensures the vehicle turns before penetrating the geofence and remains inside the allowable operational airspace by accounting for the vehicles’ turning dynamics. Allowance is made for general geozone shapes and locations, including those located at the problematic poles and meridians where nonlinear angle mapping is dealt with, concave geozones, narrow corners with acute internal angles, and transient turn dynamics. The algorithm is shown to prevent any excursions using a high-fidelity simulation of a small remotely piloted vehicle. The algorithm relies on a single tuning parameter which can be determined from the closed-loop rise time in the aircraft’s roll command tracking.

The way of using digital media based on artificial intelligence technology and the path of creation

Abstract This paper explores new approaches to the application and creation of digital media in the context of the rapid development of artificial intelligence technology, with a particular focus on virtual reality interaction. The study utilizes the spatial distance of the enclosing spheres in the hybrid hierarchical enclosing box and the characteristic of non-intersection between the enclosing boxes for collision detection, and the collision information returned by the rays is analyzed in depth. Meanwhile, the intersection test method is used to improve the efficiency of collision detection. And a subjective evaluation of 10 users’ experience in virtual reality art interaction was conducted. The results showed that the system was highly rated in accuracy (average score of 8.39), but rated lower in simplicity (average score of 4.28). There was a positive relationship between the user’s eye gaze duration and the number of interruptions and misoperations in art interactions. At an eye gaze duration of 0.2 seconds, half of the users did not experience interaction interruptions; when the gaze duration increased to 1.2 seconds, all users had no interruptions. This paper provides a practical reference case for using AI technology in digital media applications and creation, especially in enhancing the accuracy and efficiency of virtual reality interactions.

RTIndeX: Exploiting Hardware-Accelerated GPU Raytracing for Database Indexing

Data management on GPUs has become increasingly relevant due to a tremendous rise in processing power and available GPU memory. Similar to main-memory systems, there is a need for performant GPU-resident index structures to speed up query processing. Unfortunately, mapping indexes efficiently to the highly parallel and hard-to-program hardware is challenging and often fails to yield the desired performance and flexibility. Instead of proposing yet another hand-tailored index, we investigate whether we can exploit an indexing mechanism that is already built into modern GPUs: The raytracing hardware accelerator provided by NVIDIA RTX GPUs. To do so, we re-phrase the database indexing problem as a raytracing problem, where we express the dataset to be indexed as objects in a 3D scene, and point/range lookups as rays across the scene. In this combination, coined RX in the following, lookups are performed as intersection tests in hardware by dedicated raytracing cores. To analyze the pros, cons, and usefulness of the raytracing pipeline for database indexing, we carefully evaluate RX along fourteen dimensions and demonstrate its competitiveness and potential in a large variety of situations.

Building Oriented Bounding Boxes by the intermediate use of ODOPs

A myriad of intersection tests is necessary for culling algorithms to answer intersection queries in the field of ray tracing, so BVHs are employed to accelerate such queries. OBB-based BVHs usually outperform their AABB-based counterparts in terms of culling efficiency but OBBs are more expensive to compute than AABBs. On the other hand, state-of-the-art BVH builders require linear complexity OBB building algorithms. PCA-based methods run in linear time but demand high memory bandwidth and offer poorly fitting OBBs due to statistical bias. To address these problems, we propose building OBBs with the intermediate use of an orthogonal sets of polytopes (ODOPs) that stores the unbiased topological features of the mesh and enables a straightforward conversion to OBB without the need for vertex processing. This method supports both vertices and parametric differentiable swept volumes. This approach interfaces to state-of-the-art BVH builders by swapping AABBs in favor of ODOP routines. Experiments show that OBB-BVHs built using this method usually outperform AABB-BVHs in terms of SAH costs. Moreover, the OBB-BVHs tested are observed to return query results using fewer intersection tests compared to AABB-BVHs. The ODOP-BVH has been tested only on static scenes in the current version of this work.

MARF: The Medial Atom Ray Field object representation

We propose Medial Atom Ray Fields (MARFs), a novel neural object representation that enables accurate differentiable surface rendering with a single network evaluation per camera ray. Existing neural ray fields struggle with multi-view consistency and representing surface discontinuities. MARFs address both using a medial shape representation, a dual representation of solid geometry that yields cheap geometrically grounded surface normals, in turn enabling computing analytical curvature despite the network having no second derivative. MARFs map a camera ray to multiple medial intersection candidates, subject to ray-sphere intersection testing. We illustrate how the learned medial shape quantities applies to sub-surface scattering, part segmentation, and aid representing a space of articulated shapes. Able to learn a space of shape priors, MARFs may prove useful for tasks like shape retrieval and shape completion, among others. Code and data can be found at https://github.com/pbsds/MARF.

Raster Intervals: An Approximation Technique for Polygon Intersection Joins

Many data science applications, most notably Geographic Information Systems, require the computation of spatial joins between large object collections. The objective is to find pairs of objects that intersect, i.e., share at least one common point. The intersection test is very expensive especially for polygonal objects. Therefore, the objects are typically approximated by their minimum bounding rectangles (MBRs) and the join is performed in two steps. In the filter step, all pairs of objects whose MBRs intersect are identified as candidates; in the refinement step, each of the candidate pairs is verified for intersection. The refinement step has been shown notoriously expensive, especially for polygon-polygon joins, constituting the bottleneck of the entire process. We propose a novel approximation technique for polygons, which (i) rasterizes them using a fine grid, (ii) models groups of nearby cells that intersect a polygon as an interval, and (iii) encodes each interval by a bitstring that captures the overlap of each cell in it with the polygon. We also propose an efficient intermediate filter, which is applied on the object approximations before the refinement step, to avoid it for numerous object pairs. Via experimentation with real data, we show that the end-to-end spatial join cost can be reduced by up to one order of magnitude with the help of our filter and by at least three times compared to using alternative intermediate filters.

An Accelerated Hybrid Method for Electromagnetic Scattering of a Composite Target–Ground Model and Its Spotlight SAR Image

In this paper, an accelerated hybrid method of physical optics (PO) shooting and bouncing ray (SBR)–physical theory of diffraction (PTD) is proposed to deal with the electromagnetic scattering of a complex target on rough ground. To accelerate the ray tracing progress, the ray marching technique based on octree structure is employed. In this technique, only the nodes passed by the ray are detected successively until the first facet intersected by ray is found or the ray passes through the bounding box, which greatly decreases the intersection test. Then, based on the accelerated PO-SBR-PTD method, the spotlight synthetic aperture radar (SAR) echo data of the composite target–ground model is obtained by the vector superposition of the echo on each meshed patch. Furthermore, the spotlight SAR image of the composite model is simulated by the polar format algorithm (PFA). In numerical simulations, both the EM scattering of the target and composite model are calculated and evaluated by comparing with the multilevel fast multipole method (MLFMM) in FEKO software. Meanwhile the spotlight SAR image of the composite target–ground model is also compared with the real image in MSTAR data, and a satisfactory similarity between them is obtained. In addition, the SAR images of two targets on rough ground for different pose angles are also presented and analyzed.

An Accelerated SBR Method for RCS Prediction of Electrically Large Target

This letter proposes an improved shooting and bouncing ray (SBR) method to efficiently predict the radar cross (RCS) of electrically large targets. First, the scan line algorithm is used to convert three-dimensional (3-D) processing to the 2-D graphic display, which expedites the elimination of shadows. Then, the ray tracing process is accelerated by the ray-marching technique which greatly decreases the intersection test. The validity of the proposed method is verified by comparing the simulation results with those of the multilevel fast multipole method. The runtime performance contrast of the traditional Octree-SBR method and ours indicates that the accelerated algorithm is more computationally efficient. Therefore, the presented algorithm has an excellent performance in the RCS prediction of electrically large targets.

RT Engine: An Efficient Hardware Architecture for Ray Tracing

The reality of the ray tracing technology that leads to its rendering effect is becoming increasingly apparent in computer vision and industrial applications. However, designing efficient ray tracing hardware is challenging due to memory access issues, divergent branches, and daunting computation intensity. This article presents a novel architecture, a RT engine (Ray Tracing engine), that accelerates ray tracing. First, we set up multiple stacks to store information for each ray so that the RT engine can process many rays parallel in the system. The information in these stacks can effectively improve the performance of the system. Second, we choose the three-phase break method during the triangle intersection test, which can make the loop break earlier. Third, the reciprocal unit adopts the approximation method, which combines Parabolic Synthesis and Second-Degree interpolation. Combined with these strategies, we implement our system at RTL level with agile chip development. Simulation and experimental results show that our architecture achieves a performance per area which is 2.4 × greater than the best reported results for ray tracing on dedicated hardware.

Recognition model and algorithm of projectiles by combining particle swarm optimization support vector and spatial-temporal constrain

In order to improve the recognition rate and accuracy rate of projectiles in six sky-screens intersection test system, this work proposes a new recognition method of projectiles by combining particle swarm optimization support vector and spatial-temporal constrain of six sky-screens detection sensor. Based on the measurement principle of the six sky-screens intersection test system and the characteristics of the output signal of the sky-screen, we analyze the existing problems regarding the recognition of projectiles. In order to optimize the projectile recognition effect, we use the support vector machine and basic particle swarm algorithm to form a new recognition algorithm. We set up the particle swarm algorithm optimization support vector projectile information recognition model that conforms to the six sky-screens intersection test system. We also construct a spatial-temporal constrain matching model based on the spatial geometric relationship of six sky-screen intersection, and form a new projectile signal recognition algorithm with six sky-screens spatial-temporal information constraints under the signal classification mechanism of particle swarm optimization algorithm support vector machine. Based on experiments, we obtain the optimal penalty and kernel function radius parameters in the PSO-SVM algorithm; we adjust the parameters of the support vector machine model, train the test signal data of every sky-screen, and gain the projectile signal classification results. Afterwards, according to the signal classification results, we calculate the coordinate parameters of the real projectile by using the spatial-temporal constrain of six sky-screens detection sensor, which verifies the feasibility of the proposed algorithm.

System reliability analysis of a lamp problem by simulation

The paper proposes a simulation-based procedure to determine the system reliability of a lamp problem. Suppose we have k lamps to light up a room, and each lamp can light a circular area of radius r. The system reliability is the probability that there is no dark area in the room during time t. We obtain the system reliability function and the expected system lifetime through a simulation when the reliability and the coverage radius of the lamps are given. A Monte Carlo test method and an Intersection test method are used to check the system state (working or failure) for different situations. In numerical examples, Kaplan–Meier and Nelson estimators determine the system reliability function from system failure times generated by the simulation. Additionally, we compare the two methods with numerical examples.

Spelunking the deep

Neural implicit representations, which encode a surface as the level set of a neural network applied to spatial coordinates, have proven to be remarkably effective for optimizing, compressing, and generating 3D geometry. Although these representations are easy to fit, it is not clear how to best evaluate geometric queries on the shape, such as intersecting against a ray or finding a closest point. The predominant approach is to encourage the network to have a signed distance property. However, this property typically holds only approximately, leading to robustness issues, and holds only at the conclusion of training, inhibiting the use of queries in loss functions. Instead, this work presents a new approach to perform queries directly on general neural implicit functions for a wide range of existing architectures. Our key tool is the application of range analysis to neural networks, using automatic arithmetic rules to bound the output of a network over a region; we conduct a study of range analysis on neural networks, and identify variants of affine arithmetic which are highly effective. We use the resulting bounds to develop geometric queries including ray casting, intersection testing, constructing spatial hierarchies, fast mesh extraction, closest-point evaluation, evaluating bulk properties, and more. Our queries can be efficiently evaluated on GPUs, and offer concrete accuracy guarantees even on randomly-initialized networks, enabling their use in training objectives and beyond. We also show a preliminary application to inverse rendering.

A novel computative strategic planning projections algorithm (CSPPA) to generate oblique directional interference matrix for different applications in computer-aided design

Oblique-Directional Interference matrix (ODIM) is one of the important part relation models which is imperative for the assembly/disassembly sequence generation and Exploded View Generation (EVG). The automatic extraction of ODIM from a Three-Dimensional(3D) Computer-aided Design (CAD) assembly model with a large part count is computationally expensive and time-consuming. Therefore, in this paper, a novel simple yet effective method for automatic extraction of ODIM is proposed by using the contact relations, bounding box data and, the two-dimensional (2D) projections from the 3D-CAD assembly model. First, all the directions required for testing geometric feasibility are extracted using the contact relations from the selected 3D-CAD assembly model. Then, the collision detection between the parts along all the directions is tested using bounding box intersection and projection tests. Finally, the proposed method is tested on various products to create the exploded view of the 3D-CAD assembly model.

BBoxDB streams: scalable processing of multi-dimensional data streams

BBoxDB Streams is a distributed stream processing system, which allows the handling of multi-dimensional data. Multi-dimensional streams consist of n-dimensional elements, such as position data (e.g., two-dimensional positions of cars or three-dimensional positions of aircraft). The software is an enhancement of BBoxDB, a distributed key-bounding-box-value store that allows the handling of n-dimensional big data. BBoxDB Streams supports continuous range queries and continuous spatial joins; n-dimensional point and non-point data are supported. Operations in BBoxDB Streams are performed primarily on the bounding boxes of the data. With user-defined filters (UDFs), custom data formats can be decoded, and the bounding box-based operations are refined (e.g., a UDF decodes and performs intersection tests on the real geometries of WKT encoded stream elements). A unique feature of BBoxDB Streams is the ability to perform continuous spatial joins between stream elements and previously stored multi-dimensional big data. For example, the dynamic position of a car can be efficiently joined with the static spatial data of a street network.

A Simple and Efficient SBR Implementation for RCS Calculation Using Target Scaling

In order to alleviate the computational burden of the shooting and bouncing rays (SBRs) method in the radar cross section (RCS) analysis, an algorithm using target scaling is introduced in this article. This algorithm aims to reduce the number of rays that must be traced with time-consuming ray–triangle intersection tests. In order to achieve this, the target’s electrical length is reduced to a predefined value in each aspect angle. Then, only rays that hit the scaled target is traced without changing the analysis frequency. The RCS values for full-scaled model are estimated by using the ray displacements and field strengths calculated for the scaled model. This algorithm yields a significant decrease in the computational burden with a trade-off between analysis accuracy and time consumption. Analysis results show that the introduced algorithm and original SBR give very similar RCS results except at very low RCS points as depicted in the RCS versus aspect angle graphs. In addition, using a fixed frequency makes the algorithm applicable to not only perfectly electrical conducting (PEC) targets, but also targets coated with radar absorbing materials (RAMs).

Coordinate descent heuristics for the irregular strip packing problem of rasterized shapes

We consider the irregular strip packing problem of rasterized shapes, where a given set of pieces of irregular shapes represented in pixels should be placed into a rectangular container without overlap. The rasterized shapes provide simple procedures of the intersection test without any exceptional handling due to geometric issues, while they often require much memory and computational effort in high-resolution. To reduce the complexity of rasterized shapes, we propose a pair of scanlines representation called the double scanline representation that merges consecutive pixels in each row and column into strips with unit width, respectively. Based on this, we develop coordinate descent heuristics for the raster model that repeat a line search in the horizontal and vertical directions alternately, where we also introduce a corner detection technique used in computer vision to reduce the search space. Computational results for test instances show that the proposed algorithm obtains sufficiently dense layouts of rasterized shapes in high-resolution within a reasonable computation time.

Calculation model and analysis of fragment position with light field imaging mechanism under considering engineering uncertainty error factors

The spatial positions of multiple fragments formed by projectile explosion have random uncertainty dispersion state, so it is difficult to recognize each fragment and measure its spatial position when multiple fragments reach a certain area at the same time. In order to solve the problem, we propose a test method for measuring the spatial positions of multiple fragments based on dual light field intersection imaging mechanism, study refocusing principle of micro-lens array and four-dimensional light field imaging information, and establish the analytical model of spatial positions of multiple fragments. We set up the uncertainty error evaluation function of two light field cameras intersection test method from the perspective of engineering design, and give the uncertainty analysis method under engineering model. The influence of various factors on the uncertainty of test results under the engineering model is analyzed by calculation. Combined with the actual test data of the wooden target, the results show that the fragment spatial position test method based on dual light field intersection imaging mechanism is feasible and scientific.

Verbal Learning as a predictor of risks of accidents in elderly drivers.

Age-related cognitive decline impacts cognitive abilities essential for driving. We aimed to measure main cognitive functions associated with a high number of traffic violations in different driving settings. Thirty-four elderly individuals, aged between 65 and 90 years, were evaluated with a driving simulator in four different settings (Intersection, Overtaking, Rain, and Malfunction tasks) and underwent a battery of cognitive tests, including memory, attention, visuospatial, and cognitive screening tests. Individuals were divided into two groups: High-risk driving (HR, top 20% of penalty points) and normal-risk driving (NR). Non-parametric group comparison and regression analysis were performed. The HR group showed higher total driving penalty score compared to the NR group (median=29, range= 9-44 vs. median=61, range= 47-97, p<0.001). The HR group showed higher penalty scores in the Intersection task (p<0.001) and the Overtaking and Rain tasks (p<0.05 both). The verbal learning score was significantly lower in the HR group (median=33, range=12-57) compared with the NR group (median=38, range=23-57, p<0.05), and it was observed that this score had the best predictive value for worse driving performance in the regression model. General cognitive screening tests (Mini-Mental State Examination and Addenbrooke's Cognitive Evaluation) were similar between the groups (p>0.05), with a small effect size (Cohen's d=0.3 both). The verbal learning score may be a better predictor of driving risk than cognitive screening tests. High-risk drivers also showed significantly higher traffic driving penalty scores in the Intersection, Overtaking, and Rain tests.

Traffic Accident Detection Based on Deformable Frustum Proposal and Adaptive Space Segmentation

Road accident detection plays an important role in abnormal scene reconstruction for Intelligent Transportation Systems and abnormal events warning for autonomous driving. This paper presents a novel 3D object detector and adaptive space partitioning algorithm to infer traffic accidents quantitatively. Using 2D region proposals in an RGB image, this method generates deformable frustums based on point cloud for each 2D region proposal and then frustum-wisely extracts features based on the farthest point sampling network (FPS-Net) and feature extraction network (FE-Net). Subsequently, the encoder-decoder network (ED-Net) implements 3D-oriented bounding box (OBB) regression. Meanwhile, the adaptive least square regression (ALSR) method is proposed to split 3D OBB. Finally, the reduced OBB intersection test is carried out to detect traffic accidents via separating surface theorem (SST). In the experiments of KITTI benchmark, our proposed 3D object detector outperforms other state-of-the-art methods. Meanwhile, collision detection algorithm achieves the satisfactory performance of 91.8% accuracy on our SHTA dataset.