COLLISION DETECTION FOR CLOTH SIMULATION USING BOUNDING SPHERE HIERARCHY

2015 ◽  
Vol 75 (2) ◽  
Author(s):  
Abdullah Bade ◽  
Ching Sue Ping ◽  
Siti Hasnah Tanalol
Keyword(s):  
Collision Detection ◽  
Detection System ◽  
Computational Cost ◽  
Detection Algorithm ◽  
Frame Rate ◽  
Generation Process ◽  
Cloth Simulation ◽  
Real Time System ◽  
Simple Mass ◽  
Mass Spring

For the past 2-decades, the challenges of collision detection on cloth simulation have attracted numerous researchers.  Simple mass spring model is used to model the cloth where the movement of the particles within the cloth was controlled by applying the Newton’s second law. After the modeling stage, implementation of the collision detection algorithm took place on cloth has been done. The collision detection technique used is bounding sphere hierarchy. Then, quad tree is being used to partitioning the bounding sphere and the collision search was based on the top-down approach. A prototype of the collision detection system is developed on cloth simulation and several experiments were conducted. Time taken for this system to be executed is around 235.258 milliseconds. Then the frame rate is at the average of 22 frames per second which is close to the real time system. Times taken for the collision detection system travels from root to nodes were 23 seconds. As a conclusion, the computational cost for bounding sphere hierarchy is much higher because the bounding sphere required more vertices for generation process, however the execution time for bounding sphere hierarchy is faster than the AABB hierarchy.  

Efficient Half Face Detection System Based on Linear Binary Pattern

2020 ◽  
Vol 17 (5) ◽  
pp. 2342-2348
Author(s):  
Ashutosh Upadhyay ◽  
S. Vijayalakshmi
Keyword(s):  
Face Detection ◽  
Detection System ◽  
False Positive Rate ◽  
Computational Cost ◽  
Detection Algorithm ◽  
Data Set ◽  
Computation Cost ◽  
Face Features ◽  
Positive Rate ◽  
The Face

In the field of computer vision, face detection algorithms achieved accuracy to a great extent, but for the real time applications it remains a challenge to maintain the balance between the accuracy and efficiency i.e., to gain accuracy computational cost also increases to deal with the large data sets. This paper, propose half face detection algorithm to address the efficiency of the face detection algorithm. The full face detection algorithm consider complete face data set for training which incur more computation cost. To reduce the computation cost, proposed model captures the features of the half of the face by assuming that the human face is symmetric about the vertical axis passing through the nose and train the system using reduced half face features. The proposed algorithm extracts Linear Binary Pattern (LBP) features and train model using adaboost classifier. Algorithm performance is presented in terms of the accuracy i.e., True Positive Rate (TPR), False Positive Rate (FTR) and face recognition time complexity.

A Collision Detection Algorithm Using AABB and Octree Space Division

2014 ◽  
Vol 989-994 ◽  
pp. 2389-2392 ◽  
Author(s):  
Huai Yu Wang ◽  
Shu Gui Liu
Keyword(s):  
Control System ◽  
Collision Detection ◽  
Detection System ◽  
Detection Algorithm ◽  
Program Control ◽  
Space Model ◽  
Space Division ◽  
Testing Speed

NC lathe controls the action of the lathe through program control system, while programming mistakes may lead to collisions between NC lathe cutters and workpieces or fixtures. A collision detection system judge whether there are collisions ahead of time by means of reading the information of shape and pose of objects in processing environment, building a space model using CSG and acquring the movement intension of objects. Dividing the modeling space into space nodes using octree, building AABBs of objects to be tested and locating them at certain space nodes, only objects at the same node or the same father node need to be tested, thus testing speed is raised.

An FPGA-Based Real-Time Human Eye Pupil Detection System Using E2V Smart Camera

2019 ◽  
Vol 16 (2) ◽  
pp. 649-654
Author(s):  
S. Navaneethan ◽  
N. Nandhagopal ◽  
V. Nivedita
Keyword(s):  
Real Time ◽  
Detection System ◽  
Detection Algorithm ◽  
Video Frame ◽  
Smart Camera ◽  
Verilog Hdl ◽  
Real Time System ◽  
Human Eye ◽  
Pupil Detection ◽  
Main Motive

Threshold based pupil detection algorithm was found tobe most efficient method to detect human eye. An implementation of a real-time system on an FPGA board to detect and track a human's eye is the main motive to obtain from proposed work. The Pupil detection algorithm involved thresholding and image filtering. The Pupil location was identified by computing the center value of the detected region. The proposed hardware architecture is designed using Verilog HDL and implemented on aAltera DE2 cyclone II FPGA for prototyping and logic utilizations are compared with Existing work. The overall setup included Cyclone II FPGA, a E2V camera, SDRAM and a VGA monitor. Experimental results proved the accuracy and effectiveness of the hardware realtime implementation as the algorithm was able to manage various types of input video frame. All calculation was performed in real time. Although the system can be furthered improved to obtain better results, overall the project was a success as it enabled any inputted eye to be accurately detected and tracked.

A Mass-Spring Model Approach for Interactive Simulation of Wire Harnesses

2009 ◽  
Author(s):  
Shinichi Sazawa ◽  
Hideki Abe ◽  
Masayoshi Hashima ◽  
Yuichi Sato
Keyword(s):  
Differential Equation ◽  
Computational Cost ◽  
Industrial Product ◽  
Interactive Simulation ◽  
Spring Model ◽  
Cloth Simulation ◽  
Product Models ◽  
Mass Spring Model ◽  
Mass Spring ◽  
Model Approach

We present a method to simulate wire harnesses interactively, without ignoring physical accurateness. Our method relies on a mass-spring model, which is widely used in such areas as cloth simulation and hair simulation. Although a mass-spring model gives shapes of flexible objects with small computational cost, a considerable disparity of bending and stretching spring coefficients gives rise to serious instabilities of the differential equation to be solved. To solve this problem, we adopted a combination of successive leapfrog integrations and final fast projection to satisfy inextensibility. We applied this technique to simulate 3D industrial product models equipped with 20 to 30 wire harnesses and obtained a good operational response with the required physical accuracy.

An Accurate Collision Detection Method for Cable Simulation

2013 ◽  
Vol 347-350 ◽  
pp. 3571-3575
Author(s):  
Shi Fu Xie ◽  
Li Yuan Ma ◽  
Peng Yuan Liu
Keyword(s):  
Collision Detection ◽  
Detection Method ◽  
Computational Cost ◽  
Detection Algorithm ◽  
New Method ◽  
Collision Resolution ◽  
Force Method ◽  
Shortest Distance ◽  
Resolution Scheme ◽  
Cable Segment

In this paper, we present a fast and robust collision detection (CD) and resolution scheme for deformable cable using a new method based on the shortest distance of cable segment axis. We employ a bounding sphere hierarchy (BVH) by exploiting the topology of cable for reducing the collision detection query space. After searching the collision through the bounding sphere hierarchy, the collision detection algorithm will find the two segments which are close enough to require an exact collision check. Furthermore, the exact collision state is decided by our proposed method. Penalty force method is applied to the collision resolution. The comparative experiments show that the proposed method performs more accurate than existing algorithms for deformable cable simulation without substantial computational cost.

3D fabric dynamic simulation based on Mapreduce

2015 ◽  
Vol 27 (6) ◽  
pp. 793-802 ◽  
Author(s):  
Hengliang Shi ◽  
Xiaolei Bai ◽  
Jianhui Duan
Keyword(s):  
Real Time ◽  
Collision Detection ◽  
Detection Algorithm ◽  
Calculation Model ◽  
3D Animation ◽  
Content Type ◽  
Collision Response ◽  
Simulation Based ◽  
Mass Spring Model ◽  
Mass Spring

Purpose – In cloth animation field, the collision detection of fabric under external force is very complex, and difficult to satisfy the needs of reality feeling and real time. The purpose of this paper is to improve reality feeling and real-time requirement. Design/methodology/approach – This paper puts forward a mass-spring model with building bounding-box in the center of particle, and designs the collision detection algorithm based on Mapreduce. At the same time, a method is proposed to detect collision based on geometric unit. Findings – The method can quickly detect the intersection of particle and triangle, and then deal with collision response according to the physical characteristics of fabric. Experiment shows that the algorithm improves real-time and authenticity. Research limitations/implications – Experiments show that 3D fabric simulation can be more efficiency through parallel calculation model − Mapreduce. Practical implications – This method can improve the reality feeling, and reduce calculation quantity. Social implications – This collision-detection can be used into more fields such as 3D games, aero simulation training and garments automation. Originality/value – This model and method have originality, and can be used to 3D animation, digital entertainment, and garment industry.

Research on 3D Modelling and Forming Simulation of Metal Wire

2011 ◽  
Vol 383-390 ◽  
pp. 6776-6783
Author(s):  
Ming Hui Chen ◽  
Bin Yao ◽  
Rong Kun Lin ◽  
Ru Sheng Lu
Keyword(s):  
Collision Detection ◽  
Computational Cost ◽  
Detection Algorithm ◽  
3D Modelling ◽  
Machining Simulation ◽  
Machine Model ◽  
Line Segments ◽  
Forming Simulation ◽  
Geometric Patterns ◽  
Interference Test

Based on features of any shape of wire with complex geometric patterns, a method for modelling 3D wire is proposed, and the machining simulation of the 3D wire and collision detection between the wire and the machine are introduced. By using double buffering technology, we obtain smooth animation during the off-line machining simulation. The computational cost of a collision detection algorithm is decided not only by the complexity of the basic interference test used, but also by the number of times every test is applied. To simplify the collision detection algorithm, an approximate method of representing wire model and machine model by using line segments and planes is applied.

scholarly journals Concrete Crack Detection Based on Well-Known Feature Extractor Model and the YOLO_v2 Network

2021 ◽  
Vol 11 (2) ◽  
pp. 813
Author(s):  
Shuai Teng ◽  
Zongchao Liu ◽  
Gongfa Chen ◽  
Li Cheng
Keyword(s):  
Feature Extraction ◽  
Crack Detection ◽  
Computational Cost ◽  
Concrete Structures ◽  
Detection Algorithm ◽  
Computational Time ◽  
Image Size ◽  
Important Indicator ◽  
Feature Extractor ◽  
Model Training

This paper compares the crack detection performance (in terms of precision and computational cost) of the YOLO_v2 using 11 feature extractors, which provides a base for realizing fast and accurate crack detection on concrete structures. Cracks on concrete structures are an important indicator for assessing their durability and safety, and real-time crack detection is an essential task in structural maintenance. The object detection algorithm, especially the YOLO series network, has significant potential in crack detection, while the feature extractor is the most important component of the YOLO_v2. Hence, this paper employs 11 well-known CNN models as the feature extractor of the YOLO_v2 for crack detection. The results confirm that a different feature extractor model of the YOLO_v2 network leads to a different detection result, among which the AP value is 0.89, 0, and 0 for ‘resnet18’, ‘alexnet’, and ‘vgg16’, respectively meanwhile, the ‘googlenet’ (AP = 0.84) and ‘mobilenetv2’ (AP = 0.87) also demonstrate comparable AP values. In terms of computing speed, the ‘alexnet’ takes the least computational time, the ‘squeezenet’ and ‘resnet18’ are ranked second and third respectively; therefore, the ‘resnet18’ is the best feature extractor model in terms of precision and computational cost. Additionally, through the parametric study (influence on detection results of the training epoch, feature extraction layer, and testing image size), the associated parameters indeed have an impact on the detection results. It is demonstrated that: excellent crack detection results can be achieved by the YOLO_v2 detector, in which an appropriate feature extractor model, training epoch, feature extraction layer, and testing image size play an important role.

scholarly journals Gait Phase Detection Based on Muscle Deformation with Static Standing-Based Calibration

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1081
Author(s):  
Tamon Miyake ◽  
Shintaro Yamamoto ◽  
Satoshi Hosono ◽  
Satoshi Funabashi ◽  
Zhengxue Cheng ◽  
...  
Keyword(s):  
Learning Algorithm ◽  
Detection System ◽  
Calibration Method ◽  
Detection Algorithm ◽  
Video Data ◽  
Detection Accuracy ◽  
Phase Detection ◽  
Gait Phase ◽  
Logistic Regression Algorithm ◽  
Short Time

Gait phase detection, which detects foot-contact and foot-off states during walking, is important for various applications, such as synchronous robotic assistance and health monitoring. Gait phase detection systems have been proposed with various wearable devices, sensing inertial, electromyography, or force myography information. In this paper, we present a novel gait phase detection system with static standing-based calibration using muscle deformation information. The gait phase detection algorithm can be calibrated within a short time using muscle deformation data by standing in several postures; it is not necessary to collect data while walking for calibration. A logistic regression algorithm is used as the machine learning algorithm, and the probability output is adjusted based on the angular velocity of the sensor. An experiment is performed with 10 subjects, and the detection accuracy of foot-contact and foot-off states is evaluated using video data for each subject. The median accuracy is approximately 90% during walking based on calibration for 60 s, which shows the feasibility of the static standing-based calibration method using muscle deformation information for foot-contact and foot-off state detection.

scholarly journals A Vision-Based Social Distancing and Critical Density Detection System for COVID-19

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4608
Author(s):  
Dongfang Yang ◽  
Ekim Yurtsever ◽  
Vishnu Renganathan ◽  
Keith A. Redmill ◽  
Ümit Özgüner
Keyword(s):  
Visual Cues ◽  
Detection System ◽  
Critical Density ◽  
Region Of Interest ◽  
Spatial Awareness ◽  
Real Time System ◽  
Effective Measure ◽  
Social Distancing ◽  
Record Data ◽  
Real World Datasets

Social distancing (SD) is an effective measure to prevent the spread of the infectious Coronavirus Disease 2019 (COVID-19). However, a lack of spatial awareness may cause unintentional violations of this new measure. Against this backdrop, we propose an active surveillance system to slow the spread of COVID-19 by warning individuals in a region-of-interest. Our contribution is twofold. First, we introduce a vision-based real-time system that can detect SD violations and send non-intrusive audio-visual cues using state-of-the-art deep-learning models. Second, we define a novel critical social density value and show that the chance of SD violation occurrence can be held near zero if the pedestrian density is kept under this value. The proposed system is also ethically fair: it does not record data nor target individuals, and no human supervisor is present during the operation. The proposed system was evaluated across real-world datasets.

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