Hybrid Hierarchical Collision Detection Based on Data Reuse

To improve the efficiency of collision detection between rigid bodies in complex scenes, this paper proposes a method based on hybrid bounding volume hierarchies for collision detection. In order to improve the simulation performance, the method is based on weighted oriented bounding box and makes dense sampling on the convex hulls of the geometric models. The hierarchical bounding volume tree is composed of many layers. The uppermost layer adopts a cubic bounding box, while lower layers employ weighted oriented bounding box. In the meantime, the data of weighted oriented bounding box is reused for triangle intersection check. We test the method using two scenes. The first scene contains two Buddha models with totally 361,690 triangle facets. The second scene is composed of 200 models with totally 115, 200 triangle facets. The experiments verify the effectiveness of the proposed method

Quad Axis Separation Framework for Bounding-Volume Hierarchies Construction

The construction of Bounding-Volume Hierarchies (BVH) for Virtual Environment application has been varied from the rigid bodies application type to the deformable bodies application. Numerous technique and specific instruction has been given from several researchers in order to make sure that the BVH can suite their application without any restriction. In this paper, we explore the capability of BVH using a technique called Quad Axis Separation Technique (QAS) that could efficiently create full-blown hierarchical tree using approximation of separating axes theorem for Virtual Environment. A theoretical implementation is carried out with standard experimental that is also been used by researcher to test their BVH in the Virtual Environment. We also believed that QAS could provide fast and efficient hierarchical tree construction and also enhance the speed and accuracy of the collision detection technique

Separation-Sensitive Collision Detection for Convex Objects

We develop a class of new kinetic data structures for collision detection between moving convex polytopes; the performance of these structures is sensitive to the separation of the polytopes during their motion. For two convex polygons in the plane, let $D$ be the maximum diameter of the polygons, and let $s$ be the minimum distance between them during their motion. Our separation certificate changes $O(\log(D/s))$ times when the relative motion of the two polygons is a translation along a straight line or convex curve, $O(\sqrt{D/s})$ for translation along an algebraic trajectory, and $O(D/s)$ for algebraic rigid motion (translation and rotation). Each certificate update is performed in $O(\log(D/s))$ time. Variants of these data structures are also shown that exhibit \emph{hysteresis}---after a separation certificate fails, the new certificate cannot fail again until the objects have moved by some constant fraction of their current separation. We can then bound the number of events by the combinatorial size of a certain cover of the motion path by balls.Comment: 10 pages, 8 figures; to appear in Proc. 10th Annual ACM-SIAM Symposium on Discrete Algorithms, 1999; see also http://www.uiuc.edu/ph/www/jeffe/pubs/kollide.html ; v2 replaces submission with camera-ready versio

Bounding Volume Hierarchies for Collision Detection

In virtual environment world, performing collision detection between various 3D objects requires sophisticated steps to be followed in order to properly visualize their effect. It is challenging due to the fact that multiple objects undergo various motion depending on the application’s genre. It is however an essential challenge to be resolved since it’s many use in the computer animation, simulation and robotic industry. Thus, object intersection between rigid bodies has become one of the most important areas in order to bring realism to simulation and animation

Quad Separation Algorithm for Bounding-Volume Hierarchies Construction in Virtual Environment Application

In order to perform fast collision detection technique in Virtual Environment Application, researchers need to maintain the behaviour of the object itself before the objects come into contact. By enhancing the speed of intersection using Bounding-Volume Hierarchies technique, it helps to reduce the complexity and speed up the intersection process. Thus, in this paper we presented our novel algorithm for constructing Bounding-Volume Hierarchies using Quad Splitting method. Together with the Quad Splitting method is the implementation of Spatial Object Median Splitting technique (SOMS) in order to create a well-balanced tree for the object. We believed the key of performing fast intersection between two or more objects in Virtual Environment Application required a well-balanced and proper tree technique for Bounding-Volume hierarchies

Bounding Volume Hierarchies for Collision Detection

In virtual environment world, performing collision detection between various 3D objects requires sophisticated steps to be followed in order to properly visualize their effect. It is challenging due to the fact that multiple objects undergo various motion depending on the application’s genre. It is however an essential challenge to be resolved since it’s many use in the computer animation, simulation and robotic industry. Thus, object intersection between rigid bodies has become one of the most important areas in order to bring realism to simulation and animation

The Construction of Balanced Bounding-Volume Hierarchies using Spatial Object Median Splitting Method for Collision Detection

Finding two or more contact points between rigid bodies simulation is always a fundamental task in virtual environment. Furthermore, the contact point needs to be accurately reported as soon as possible within 30-60 frames per second (fps) between moving polyhedral. This article introduced an efficient splitting method that is able to divide the bounding-volume of Axis Aligned Bounding-Box (AABB) hierarchies into a balanced tree. The construction of well-balanced tree will helps to improve the speed of the intersection between rigid bodies’ objects

S-OHEM: Stratified Online Hard Example Mining for Object Detection

One of the major challenges in object detection is to propose detectors with highly accurate localization of objects. The online sampling of high-loss region proposals (hard examples) uses the multitask loss with equal weight settings across all loss types (e.g, classification and localization, rigid and non-rigid categories) and ignores the influence of different loss distributions throughout the training process, which we find essential to the training efficacy. In this paper, we present the Stratified Online Hard Example Mining (S-OHEM) algorithm for training higher efficiency and accuracy detectors. S-OHEM exploits OHEM with stratified sampling, a widely-adopted sampling technique, to choose the training examples according to this influence during hard example mining, and thus enhance the performance of object detectors. We show through systematic experiments that S-OHEM yields an average precision (AP) improvement of 0.5% on rigid categories of PASCAL VOC 2007 for both the IoU threshold of 0.6 and 0.7. For KITTI 2012, both results of the same metric are 1.6%. Regarding the mean average precision (mAP), a relative increase of 0.3% and 0.5% (1% and 0.5%) is observed for VOC07 (KITTI12) using the same set of IoU threshold. Also, S-OHEM is easy to integrate with existing region-based detectors and is capable of acting with post-recognition level regressors.Comment: 9 pages, 3 figures, accepted by CCCV 201

Fast Penetration Depth Estimation for Elastic Bodies

We present a fast penetration depth estimation algorithm between deformable polyhedral objects. We assume the continuum of non-rigid models are discretized using standard techniques, such as finite element or finite difference methods. As the objects deform, the pre-computed distance fields are deformed accordingly to estimate penetration depth, allowing enforcement of non-penetration constraints between two colliding elastic bodies. This approach can automatically handle self-penetration and inter-penetration in a uniform manner. We demonstrate its effectiveness on moderately complex simulation scenes