Intersection Detection Research Articles

GPU Accelerated Real-Time Collision Handling in Virtual Disassembly

Previous collision detection methods for virtual disassembly mainly detect collisions at discrete time intervals, and use oriented bounding boxes to speed up the process. However, these discrete methods cannot guarantee no penetration occurs when the components move. Meanwhile, because some of the components are embedded into each other, these components cannot be separated in the subsequent process. To solve these problems, we propose an approach for real-time collision handling by utilizing the computational power of modern GPUs. First we present a novel GPU-based collision handling framework for virtual disassembly. Second we use a collision-streams based continuous collision detection to guarantee no collision missed. Finally we introduce a triangle intersection detection algorithm to solve the problem that collision cannot be detected when the components are embedded into each other at the initial configuration. The experimental results show that our method can improve the overall performance of collision detection and achieve real-time simulation.

GRowing Algorithm for Intersection Detection (GRAID) in branching patterns

Analysis of branching structures represents a very important task in fields such as medical diagnosis, road detection or biometrics. Detecting intersection landmarks becomes crucial when capturing the structure of a branching pattern. We present a very simple geometrical model to describe intersections in branching structures based on two conditions: Bounded Tangency (BT) condition and Shortest Branch (SB) condition. The proposed model precisely sets a geometrical characterization of intersections and allows us to introduce a new unsupervised operator for intersection extraction. We propose an implementation that handles the consequences of digital domain operation that, unlike existing approaches, is not restricted to a particular scale and does not require the computation of the thinned pattern. The new proposal, as well as other existing approaches in the bibliography, are evaluated in a common framework for the first time. The performance analysis is based on two manually segmented image data sets: DRIVE retinal image database and COLON-VESSEL data set, a newly created data set of vascular content in colonoscopy frames. We have created an intersection landmark ground truth for each data set besides comparing our method in the only existing ground truth. Quantitative results confirm that we are able to outperform state-of-the-art performance levels with the advantage that neither training nor parameter tuning is needed.

Abnormal Event Detection of Traffic Intersection Based on SAT Algorithm

SAT (Separating Axis Theorem) is an algorithm applied in two-dimensional games of collision detection in the convex polygon. This paper applied SAT algorithm into video monitoring at intersections to detect the vehicles collision incidents. Established separation axis to extracted vehicles and projected the target vehicles into separation axis. Through comparing the scalar value in separation axis to determine whether the target vehicles collision. It's proved that the method is effective by using Matlab software to the simulation test in this algorithm.

A robust method for scale independent detection of curvature-based criticalities and intersections in line drawings

A novel two-phase iterative method is proposed to identify curvature based criticalities and intersections in line drawings. The method is based on evaluating a field obtained from the image via diffusion using adaptively changing ellipse-shaped analysis windows. The deviation of the average field strength values within the analysis windows from that of an external reference field is used as a metric to evaluate the criticality of a region. The external reference field is computed from an image of a straight line. The experimental results depict that the method is effective in detecting curvature based criticalities and intersections, even for noisy and disconnected drawings as well as drawings drawn with a variety of brush characteristics, such as glass, ocean, ripple, scatter, stamp, strokes effects. Our method can be employed as a part of a design grammar interpreter.

Road intersection detection and classification using hierarchical SVM classifier

In this paper, a hierarchical multi-classification approach using support vector machines (SVM) has been proposed for road intersection detection and classification. Our method has two main steps. The first involves the road detection. For this purpose, an edge-based approach has been developed using the bird’s eye view image which is mapped from the perspective view of the road scene. Then, the concept of vertical spoke has been introduced for road boundary form extraction. The second step deals with the problem of road intersection detection and classification. It consists on building a hierarchical SVM classifier of the extracted road forms using the unbalanced decision tree architecture. Many measures are incorporated for good evaluation of the proposed solution. The obtained results are compared to those of Choi et al. (2007).

Intersection detection and recognition for autonomous urban driving using a virtual cylindrical scanner

In this study, the authors propose an effective real-time approach for intersection detection and recognition during autonomous driving in an unknown urban environment. The authors approach use point cloud data acquired by a three-dimensional laser scanner mounted on the vehicle. Intersection detection and recognition are formulated as a classification problem whereby roads are classified as segments or intersections and intersections are subclassified as T-shaped or +-shaped. They first construct a novel model called a virtual cylindrical scanner for efficient feature-level representation of the point cloud data. Then they use support vector machine classifiers to resolve the classification problem according to the features extracted. A series of experiments on real-world data sets and in a simulation environment demonstrate the effectiveness and robustness of the authors approach, even in highly dynamic urban environment. They also performed simulation experiments to investigate effects of several critical factors on their proposed approach, such as other vehicles on the road and the advance detection distance.

Offsetting obstacles of any shape for robot motion planning

SUMMARYWe present an algorithm for offsetting the workspace obstacles of a circular robot. Our method has two major steps: It finds the raw offset curve for both lines and circular arcs, and then removes the global invalid loops to find the final offset. To generate the raw offset curve and remove global invalid loops, O(n) and O((n+k)log m) computational times are needed respectively, where n is the number of vertices in the original polygon, k is the number of self-intersections and m is the number of segments in the raw offset curve, where m ≤ n. Any local invalid loops are removed before generating the raw offset curve by invoking a pair-wise intersection detection test (PIDT). In the PIDT, two intersecting entities are checked immediately after they are computed, and if the test is positive, portions of the intersecting segments are removed. Our method works for conventional polygons as well as the polygons that contain circular arcs. Our algorithm is simple and very fast, as each sub-process of the algorithm can be completed in linear time except the last one, which is nearly linear. Therefore, the overall complexity of the algorithm is nearly linear. By applying our simple and efficient approach, offsetting obstacles of any shape make it possible to construct a configuration space that ensures optimized motion planning.

Experimental Analysis of Various Types of Road Intersections for Interchange Detection

AbstractRoad interchanges are a major pattern type in road networks. Recognition of road interchanges benefits automated road network generalization, car navigation and traffic flow analysis. This study first investigated several existing approaches to automatically detecting interchanges in a road network, and determined that the recognition of characteristic road intersections is essential for the effective detection of interchanges. Several experiments were carried out to investigate nine types of road intersections for interchange detection and to analyze characteristic ones. Furthermore, an approach to the detection of both intersections and segments of interchanges was proposed and validated. The road networks across different scales were tested and results show that: (1) the T‐shaped and Cross‐shaped junctions are very common in road networks, but they are not the most characteristic ones for interchange detection; (2) the y‐shaped, Y‐shaped types, X‐shaped, Fork‐shaped and Multi‐leg may be the characteristic types for interchange detection; (3) the proposed approach to detecting interchanges is effective, and most of the intersections and segments of interchanges can be detected. In addition, taking multiple characteristic types into consideration for interchange detection is suggested.

An Efficient Astronomical Image Representation for Solar System Object Searches

Astronomical images are typically thought of as two-dimensional rectangular projections onto the celestial sphere. Such images may be defined by the right ascension (α) and declination (δ) of the four corners of the image, or by the α and δ of the image center, width and height of the image, and the rotation around the image center. The computations involved in determining the location of a moving object in relation to an image exposure involves several conversions of the object’s position into observer centered α and δ as both the object and observer move over time. These conversions, although not complex, are computationally expensive as they involve trigonometric transformations. Since the position of an object is relative to the observer, there is little opportunity to optimize this heavy computation against multiple images, or against multiple image collections. The viewing frustum, the three-dimensional volume of space covered by an observer’s view of a scene, is a long-used computer scene-rendering tool that allows world object positions to be transformed and clipped to a viewing port. This tool has been adapted to represent astronomical images as image frustums, supporting a one-time presearch optimization of individual image representations, while dramatically reducing object-image intersection detection complexity.

Triangle-Triangle Intersection Determination and Classification to Support Qualitative Spatial Reasoning

In CAD/CAM modeling, objects are represented using the Boundary Representation (ANSI Brep) model. Detection of possible intersection between objects can be based on the objects' boundaries (i.e., triangulated surfaces), and computed using triangle-triangle intersection. Usually only a cross intersection algorithm is needed; however, it is beneficial to have a single robust and fast intersection detection algorithm for both cross and coplanar intersections. For qualitative spatial reasoning, a general-purpose algorithm is desirable for accurately differentiating the relations in a region connection calculus, a task that requires consideration of intersection between objects. Herein we present a complete uniform integrated algorithm for both cross and coplanar intersection. Additionally, we present parametric methods for classifying and computing intersection points. This work is applicable to most region connection calculi, particularly VRCC-3D+, which detects intersections between 3D objects as well as their projections in 2D that are essential for occlusion detection.

Evaluation of Mesostructure of Particulate Composites by Quantitative Stereology and Random Sequential Packing Model of Mono-/Polydisperse Convex Polyhedral Particles

Random packing of particles has served as a topic of intense research in the chemical, physical, engineering, and material fields. The majority of previous works focused on the random packing models of spherical, cylindrical, and ellipsoidal particles, whereas little is known about polyhedral particles. In this article, a modeling study of the random packing of convex polyhedral particles is presented in detail, using an interparticle contact detection algorithm, a particle-to-container wall intersection detection algorithm, and a random sequential packing algorithm for hard particles, and the accuracy and efficiency of the contact detection algorithm are compared with those of methods from the literature. With the random packing model and a specified particle size distribution, mesostructure models of particulate composites with mono-/polydisperse particles were generated and validated by a sectioning analysis algorithm. Based on quantitative stereological theories and the sectioning analysis algorithm, the effects of particle shape on the mesostructures composed of the monodisperse and polydisperse particles were evaluated. Further, the statistical results were verified by validation against experimental results from the literature and theoretical results.

Efficient Implementation of Finite Element Methods on Nonmatching and Overlapping Meshes in Three Dimensions

In recent years, a number of finite element methods have been formulated for the solution of partial differential equations on complex geometries based on nonmatching or overlapping meshes. Examples of such methods are the fictitious domain method, the extended finite element method, and Nitsche's method. In all these methods, integrals must be computed over cut cells or subsimplices, which is challenging to implement, especially in three space dimensions. In this note, we address the main challenges of such an implementation and demonstrate good performance of a fully general code for automatic detection of mesh intersections and integration over cut cells and subsimplices. As a canonical example of an overlapping mesh method, we consider Nitsche's method, which we apply to Poisson's equation and a linear elastic problem.

MULTOVL: fast multiple overlaps of genomic regions

We present the MULTOVL application suite that detects and statistically analyses multiple overlaps of genomic regions in a fast and efficient manner. The package supports the detection of multiple region intersections, unions and 'solitary' genomic regions. The significance of actually observed overlaps is estimated by comparing them with empirical null distributions generated by random shuffling of the input regions.

方位検出と交差点認識を用いた道なり走行ベースの屋外自律ナビゲーション

方位検出と交差点認識を用いた道なり走行ベースの屋外自律ナビゲーション

Real-time isosurface rendering of smooth fields

This paper presents a new technique for real-time isosurface visualization of three-dimensional smooth fields. This technique enables direct isosurface rendering of smoothly defined fields without generating intermediate polygon models as used in the marching-cube algorithm, a standard technique for isosurface extraction. We developed a parallel algorithm that is suitable for effective computation on graphics hardware by converting any field to a set of polynomials, enabling the detection of intersections between rays and isosurfaces at arbitrary isovalue with small computational cost. In addition, the isovalue to be rendered can be changed in real time, because the algorithm is not restricted to a specific isovalue. The technique can also be applied to the problem of the direct rendering of implicit surfaces that are defined as isosurfaces of smoothly defined fields.

Automatic Acquisition of Corpus for Multimedia Applications

Evaluations of tools (information retrieval systems, machine learning, speech recognition, machine translation, automatic acquisition of data, etc.) are annually organized throughout evaluation campaigns (TREC, ELRA, ESTER IWSLT, etc.). The building of an ad hoc evaluation corpus in the context of these evaluation campaigns is a complex task and it is done manually today and with a high cost. Indeed, this is a very dedicated corpus that would answer to an application need in a precise context but automating its building is a challenge that will help significantly the organization of these campaigns. As a contribution to this challenge, we propose in a context of multimedia information retrieval, an approach of multilevel extension of a small applicative corpus to a larger and voluminous corpus based on the detection of intersections between the two corpus in terms of lemmas having the same grammatical label, that means to get a list of appropriate terminology for which we use several tools (internal and external to our laboratory) and we try to evaluate them in order to keep consistency and coherence with the original corpus..

Collision and intersection detection of two ruled surfaces using bracket method

Collision and intersection detection of surfaces is an important problem in computer graphics and robotic engineering. A key idea of our paper is to use the bracket method to derive the necessary and sufficient conditions for the collision of two ruled surfaces. Then the numerical intersection curve can be characterized. The cases for two bounded ruled surfaces are also discussed.

RETINA FUNDUS IMAGE MASK GENERATION USING PSEUDO PARAMETRIC MODELING TECHNIQUE

The use of vascular intersection as one of the symptomsfor monitoring and diagnosis of diabetic retinopathy fromfundus images have been widely reported in literatures. Inthis work, a new hybrid approach that makes use of threedifferent methods of vascular intersection detection namelyModified cross-point number (MCN), Combine Cross Points(CNN) and Artificial Neural Network (ANN) is hereby proposed.Result obtained from the application of this techniqueto both simulated and experimental shows a very high accuracyand precision value in detecting both bifurcation andcross over points. Thus an improvement in bifurcation andvascular point detection and a good tool in the monitoringand diagnosis of diabetic retinopathy.

Foreword

In the last years, the field of non-linear Computational Geometry has produced very relevant algorithmic advances, for instance, by adapting to low-degree curved objects techniques dealing with linear primitives. Moreover the introduction of new algorithms and approaches for dealing efficiently with curves and surfaces has shown a considerable impact in fields such as Computer-Aided Design where final users are continuously demanding more efficiency, accuracy, robustness, etc. New approaches for solving geometric problems, coming from Computer-Aided Geometric Design and involving curves and surfaces with a Computational Geometry flavour is the main focus of this special issue. Contributions were asked in areas such as: arrangements of low degree curves and surfaces; Voronoi diagrams and medial axes involving curved ob jects; offset computations and their topology; distance predicates for curves and surfaces; closed formulae for geometric queries involving curves and surfaces; intersection detection for moving curved ob jects; adapting algebraic or geometrical techniques for solving algorithmic problems involving curves and surfaces. This special issue is a direct consequence of the Second International Conference on Mathematical Aspects of Computer and Information Sciences - MACIS 2007 (see http:// www- spiral.lip6.fr/ MACIS2007) held in Paris in December 2007 and where Computational Geometry and Computer Aided Geometric Design were one of the main topics (among other two, Polynomial System Solving and Algorithms and Complexity). Finally six papers (out of eight papers submitted by the March 2009 deadline) were finally accepted. The two papers by C. D'Andrea et al. and I. Z. Emiris et al. deal with the problem of analyzing the Newton polygon of the implicit equation of a rational curve starting from its parameterization: both papers are devoted to study from different viewpoints the properties of the set of monomials appearing in the implicit equation of the considered curve without computing it. The two papers by E. Berberich et al. introduce a new approach to deal with the problem of determining the shape of an arrangement of curves on several classes of parametric surfaces which is then applied to compute, for example, the Minkowski sum of polytopes or the envelope of surfaces. The two papers by D. Lazard and J. Cheng et al. deal with the problem of computing the topology of a semialgebraic set (i.e. a set in $\mathbb{R}^n$ defined by polynomial equations and inequations): the first one shows how to deal with the general case by using the so called Cylindrical Algebraic Decomposition and the second one introduces an extremely fast algorithm computing the topology of a real algebraic plane curve defined implicitely. We would like finally to thank all the reviewers who definitively helped with their work to improve the papers that appear into this special issue.

Irregular Packing Using the Line and Arc No-Fit Polygon

The no-fit polygon is a geometric construct that can offer faster and more efficient handling of geometry between pairs of shapes than traditional line-by-line intersection. The detection of intersections is a critical operation within the irregular two-dimensional stock-cutting problem (also known as “nesting”), which aims to place shapes onto sheets of material so that the material is utilised as efficiently as possible and the waste (or trim loss) is reduced. The problem forms an important process within many real-world manufacturing industries such as metalworking, automotive production, aerospace, clothing and conservatory manufacture, and others. If manufacturers can reduce their costs by utilising raw materials more effectively, this can directly translate into increased profit margins or greater competitiveness within the marketplace. Moreover, there are significant environmental benefits to be gained. Several methods have been proposed to calculate no-fit polygons, but most, if not all, can only operate on geometry that consists of line segments. This paper extends the orbital sliding method of calculating no-fit polygons to enable it to handle arcs and then shows the resultant no-fit polygons being utilised successfully on the two-dimensional irregular packing problem. As far as the authors are aware, this is the first time that a no-fit polygon algorithm has been able to handle arcs robustly without decomposing to their line approximations. The modification of the authors' previously published packing algorithm to utilise the proposed no-fit polygon approach yields solutions of excellent quality (including several best-known) on well-established literature benchmark problems after only a few minutes. The authors believe that the success of the packing strategy and the line and arc no-fit polygon algorithm make this approach a serious candidate for use in real-world production environments.