Hardware-Based Collision and Self-Collision for Rigid and Deformable Surfaces

2004 ◽  
Vol 13 (6) ◽  
pp. 681-691 ◽  
Author(s):  
Wingo Sai-Keung Wong ◽  
George Baciu
Keyword(s):  
Virtual Environments ◽  
Collision Detection ◽  
Detection System ◽  
Graphics Hardware ◽  
Detection Algorithms ◽  
Novel Technique ◽  
Deformable Surfaces ◽  
Triangular Elements ◽  
Bounding Boxes ◽  
Object Level

The interactive requirements of 3D games and physically driven virtual environments add strong constraints to the simulation of natural cloth collisions and self-collisions. In order to achieve interactive rates, we first define smoothness conditions over small patches of deformable surfaces and then resort to image-based collision-detection algorithms that we have developed. Our collision-detection system achieves interactive rates as it accurately tracks collisions and self-interactions of objects consisting of highly deformable surfaces. This method makes use of a novel technique for dynamically generating a hierarchy of cloth bounding boxes in order to perform object-level culling and image-based intersection tests using conventional graphics hardware support. Our results show that, for complex deformable surfaces with an excess of 50,000 triangular elements, we can track collisions at nearly interactive rates.

Interactive Simulation of Complex Audiovisual Scenes

2004 ◽  
Vol 13 (1) ◽  
pp. 99-111 ◽  
Author(s):  
Kees van den Doel ◽  
Dave Knott ◽  
Dinesh K. Pai
Keyword(s):  
Closed Form ◽  
Collision Detection ◽  
Rigid Bodies ◽  
Particle Simulation ◽  
Graphics Hardware ◽  
Interactive Simulation ◽  
Novel Technique ◽  
Modal Synthesis ◽  
Human Ear

We demonstrate a method for efficiently rendering the audio generated by graphical scenes with a large number of sounding objects. This is achieved by using modal synthesis for rigid bodies and rendering only those modes that we judge to be audible to a user observing the scene. We show how excitations of modes can be estimated and inaudible modes eliminated based on the masking characteristics of the human ear. We describe a novel technique for generating contact events by performing closed-form particle simulation and collision detection with the aid of programmable graphics hardware. The effectiveness of our system is shown in the context of suitably complex simulations.

Efficient Collision Culling among Deformable Objects using Graphics Processors

2006 ◽  
Vol 15 (1) ◽  
pp. 62-76 ◽  
Author(s):  
Naga K. Govindaraju ◽  
Ming C. Lin ◽  
Dinesh Manocha
Keyword(s):  
Collision Detection ◽  
Classification Scheme ◽  
Graphics Hardware ◽  
Graphics Processors ◽  
Close Proximity ◽  
Complex Models ◽  
Computation Algorithm ◽  
Geometric Primitives ◽  
Object Level ◽  
Fast Collision

We present a fast collision culling algorithm for performing inter- and intra-object collision detection among complex models using graphics hardware. Our algorithm utilizes visibility queries on the GPUs to eliminate a subset of geometric primitives that are not in close proximity and computes a potentially colliding set (PCS) of primitives. We perform no precomputation and the algorithm proceeds in multiple stages: object-level PCS computation, subobject level PCS computation, followed by exact collision detection. We extend our PCS computation algorithm to perform intra-object or self-collisions between complex models. Furthermore, we describe a novel visibility-based classification scheme to reduce the size of potentially-colliding sets of objects and primitives, and the number of visibility queries for further improving the performance and culling efficiency. We have implemented our algorithm on a PC with an NVIDIA GeForce FX 6800 Ultra graphics card and applied it to three complex simulations, each consisting of objects with tens of thousands of triangles. In practice, we are able to compute all the self-collisions for cloth simulation up to image-space precision at interactive rates.

scholarly journals Multi-Scale Feature Pyramid Network: A Heavily Occluded Pedestrian Detection Network Based on ResNet

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1820
Author(s):  
Xiaotao Shao ◽  
Qing Wang ◽  
Wei Yang ◽  
Yun Chen ◽  
Yi Xie ◽  
...  
Keyword(s):  
Semantic Information ◽  
Detection System ◽  
Pedestrian Detection ◽  
Detection Accuracy ◽  
The Public ◽  
Scale Feature ◽  
Detection Algorithms ◽  
Multi Scale ◽  
Art Works ◽  
Feature Pyramid

The existing pedestrian detection algorithms cannot effectively extract features of heavily occluded targets which results in lower detection accuracy. To solve the heavy occlusion in crowds, we propose a multi-scale feature pyramid network based on ResNet (MFPN) to enhance the features of occluded targets and improve the detection accuracy. MFPN includes two modules, namely double feature pyramid network (FPN) integrated with ResNet (DFR) and repulsion loss of minimum (RLM). We propose the double FPN which improves the architecture to further enhance the semantic information and contours of occluded pedestrians, and provide a new way for feature extraction of occluded targets. The features extracted by our network can be more separated and clearer, especially those heavily occluded pedestrians. Repulsion loss is introduced to improve the loss function which can keep predicted boxes away from the ground truths of the unrelated targets. Experiments carried out on the public CrowdHuman dataset, we obtain 90.96% AP which yields the best performance, 5.16% AP gains compared to the FPN-ResNet50 baseline. Compared with the state-of-the-art works, the performance of the pedestrian detection system has been boosted with our method.

Structural Design of Intrusion Detection System

2014 ◽  
Vol 530-531 ◽  
pp. 705-708
Author(s):  
Yao Meng
Keyword(s):  
Intrusion Detection ◽  
Structural Design ◽  
Intrusion Detection System ◽  
Detection System ◽  
Algorithm Design ◽  
Detection Algorithm ◽  
Attack Detection ◽  
Detection Algorithms ◽  
Defense Systems ◽  
Ddos Attack Detection

This paper first engine starting defense from Intrusion Detection, Intrusion detection engine analyzes the hardware platform, the overall structure of the technology and the design of the overall structure of the plug, which on the whole structure from intrusion defense systems were designed; then described in detail improved DDOS attack detection algorithm design thesis, and the design of anomaly detection algorithms.

scholarly journals Dog Face Detection Using YOLO Network

MENDEL ◽  
2020 ◽  
Vol 26 (2) ◽  
pp. 17-22
Author(s):  
Alzbeta Tureckova ◽  
Tomas Holik ◽  
Zuzana Kominkova Oplatkova
Keyword(s):  
Face Detection ◽  
Detection System ◽  
Training Procedure ◽  
The Gaze ◽  
Real World Application ◽  
Human Face Detection ◽  
Deep Convolution Neural Network ◽  
Bounding Boxes ◽  
The Moment ◽  
Different Sources

This work presents the real-world application of the object detection which belongs to one of the current research lines in computer vision. Researchers are commonly focused on human face detection. Compared to that, the current paper presents a challenging task of detecting a dog face instead that is an object with extensive variability in appearance. The system utilises YOLO network, a deep convolution neural network, to~predict bounding boxes and class confidences simultaneously. This paper documents the extensive dataset of dog faces gathered from two different sources and the training procedure of the detector. The proposed system was designed for realization on mobile hardware. This Doggie Smile application helps to snapshot dogs at the moment when they face the camera. The proposed mobile application can simultaneously evaluate the gaze directions of three dogs in scene more than 13 times per second, measured on iPhone XR. The average precision of the dogface detection system is 0.92.

scholarly journals Efficient n-to-n Collision Detection for Space Debris using 4D AABB Trees

10.29007/5pl1 ◽  
2019 ◽  
Author(s):  
Stanley Bak ◽  
Kerianne Hobbs
Keyword(s):  
Collision Detection ◽  
Space Debris ◽  
Dynamics Simulation ◽  
Video Gaming ◽  
Time Dimension ◽  
Detection Algorithms ◽  
Space Objects ◽  
Tree Data ◽  
Tree Data Structure ◽  
Three Space

Collision detection algorithms are used in aerospace, swarm robotics, automotive, video gaming, dynamics simulation and other domains. As many applications of collision detection run online, timing requirements are imposed on the algorithm runtime: algorithms must, at a minimum, keep up with the passage of time. Even offline reachability computation can be slowed down by the process of safety checking when n is large and the specification is n-to-n collision avoidance. In practice, this places a limit on the number of objects, n, that can be concurrently tracked or verified. In this paper, we present an improved method for efficient object tracking and collision detection, based on a modified version of the axis-aligned bounding-box (AABB) tree data structure. We consider 4D AABB Trees, where a time dimension is added to the usual three space dimensions, in order to enable per-object time steps when checking for collisions in space-time. We evaluate the approach on a space debris collision benchmark, demonstrating efficient checking beyond the full catalog of n = 16848 space objects made public by the U.S. Strategic Command on www.space-track.org.

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