scholarly journals Badminton motion capture with visual image detection of picking robotics

2020 ◽  
Vol 17 (6) ◽  
pp. 172988142096907
Author(s):  
Changxin Li
Keyword(s):  
Image Processing ◽  
Control System ◽  
Motion Capture ◽  
High Precision ◽  
Target Recognition ◽  
Vision System ◽  
Recognition Rate ◽  
Motion Capture System ◽  
Vision Control ◽  
Edge Features

In the process of strawberry easily broken fruit picking, in order to reduce the damage rate of the fruit, improves accuracy and efficiency of picking robot, field put forward a motion capture system based on international standard badminton edge feature detection and capture automation algorithm process of night picking robot badminton motion capture techniques training methods. The badminton motion capture system can analyze the game video in real time and obtain the accuracy rate of excellent badminton players and the technical characteristics of badminton motion capture through motion capture. The purpose of this article is to apply the high-precision motion capture vision control system to the design of the vision control system of the robot in the night picking process, so as to effectively improve the observation and recognition accuracy of the robot in the night picking process, so as to improve the degree of automation of the operation. This paper tests the reliability of the picking robot vision system. Taking the environment of picking at night as an example, image processing was performed on the edge features of the fruits picked by the picking robot. The results show that smooth and enhanced image processing can successfully extract edge features of fruit images. The accuracy of the target recognition rate and the positioning ability of the vision system of the picking robot were tested by the edge feature test. The results showed that the accuracy of the target recognition rate and the positioning ability of the motion edge of the vision system were far higher than 91%, satisfying the automation demand of the picking robot operation with high precision.

Vehicle Security Distance Control Based on Binocular Parallax Vision

2014 ◽  
Vol 644-650 ◽  
pp. 207-210
Author(s):  
Shuang Liu ◽  
Xiang Jie Kong ◽  
Ming Cai Shan
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
High Precision ◽  
Stereo Matching ◽  
Vision System ◽  
Intelligent Transportation ◽  
Distance Control ◽  
Calibration Methods ◽  
Computer Vision Technology ◽  
Vehicle Security

Binocular parallax vision system is a kind of computer vision technology. Two cameras on different locations can get two different pictures of same object. The space position of the object can be calculated by the parallax information of two different pictures. The binocular parallax vision technology includes cameras calibration, image processing, and stereo matching analysis. The paper will introduce the inside and outside parameters calibration methods, and combing the traffic applications, designed the calibrating scheme. The parameters that obtained according to the scheme can meet the demands of measuring the vehicle distance. The high precision can meet the needs of intelligent transportation vehicles in a security vehicles spacing survey, which is an effective way for measuring the front car distance.

scholarly journals Mathematical Modeling and Simulation of Table Tennis Trajectory Based on Digital Video Image Processing

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Chuan He ◽  
Xiaoquan Zhang ◽  
Yulong Gui ◽  
Yang Liu ◽  
Wei Zhang
Keyword(s):  
Image Processing ◽  
Motion Capture ◽  
Domain Knowledge ◽  
Digital Video ◽  
Motion Capture System ◽  
Table Tennis ◽  
Sports Training ◽  
Inertial Motion ◽  
Movement Characteristics ◽  
Video Image Processing

Digital sports training based on digital video image processing promises to reduce the reliance on the experience of coaches in the table tennis training process and to achieve a more general physical education base. Based on this approach, this paper describes the specific forms of exercise content, movement characteristics, and skill levels in the table tennis framework and specifies the calculation methods of motion capture and movement characteristics suitable for table tennis. Meanwhile, to further improve the accuracy of the inertial motion capture system in restoring the position posture of the trainees, this paper improves the original inertial motion capture system from two aspects: contact judgment of both feet and correction of the position posture based on the contact position constraint. The simulation results show that the corrected human posture has good action smoothness. This paper first proposes a knowledge-based generic sports-assisted training framework based on generalizing the traditional sports training model. The framework contains four main modules: domain knowledge, trainees, sport evaluation, and controller. The domain knowledge module is a digital representation of the knowledge of the exercise content, improvement instructions, and skill indicators of the sport; the trainee module is the active response of the trainee to the exercise content and improvement instructions; the motion evaluation module uses motion capture technology to obtain the raw motion data of the trainee and further calculates the motion characteristics; the controller module proposes improvement instructions to the trainee or makes him/her practice new content based on the results of the motion evaluation. Based on the results of the motion evaluation, the controller module proposes improvement instructions or makes the trainee practice new content until the trainee achieves the desired goal.

The Recognition of Smart Car Track and Starting Line

2011 ◽  
Vol 308-310 ◽  
pp. 833-836
Author(s):  
Wen Dai ◽  
Ming Ge Cao ◽  
Xu Ying Ren
Keyword(s):  
Image Processing ◽  
Control System ◽  
Recognition Rate ◽  
Processing Method ◽  
Experimental Results ◽  
Recognition Method ◽  
Image Processing Method ◽  
Main Track ◽  
The Given ◽  
Motor Controls

In this paper, an intelligent car control system based on MCU is proposed. A camera mounted on the car is used to capture path images, in which path is recognized by image processing method. Based on the extracted path information, the car motor controls are applied to keep car running in the given path. The recognition rate and precision of main track and starting line will directly affect the precision of control system. In this article, a recognition method is proposed, and experimental results show that our car can follow the main track and stopped on the starting line.

A Hierarchical Target Recognition Method Based on Image Processing

2017 ◽  
pp. 91-107
Author(s):  
QingE Wu ◽  
Weidong Yang
Keyword(s):  
Image Processing ◽  
Feature Extraction ◽  
Target Recognition ◽  
Wavelet Packet ◽  
Recognition Rate ◽  
Image Decomposition ◽  
Extraction Process ◽  
Practical Significance ◽  
Recognition Method ◽  
Target Feature

In order to provide an accurate and rapid target recognition method for some military affairs, public security, finance and other departments, this paper studies firstly a variety of fuzzy signal, analyzes the uncertainties classification and their influence, eliminates fuzziness processing, presents some methods and algorithms for fuzzy signal processing, and compares with other methods on image processing. Moreover, this paper uses the wavelet packet analysis to carry out feature extraction of target for the first time, extracts the coefficient feature and energy feature of wavelet transformation, gives the matching and recognition methods, compares with the existing target recognition methods by experiment, and presents the hierarchical recognition method. In target feature extraction process, the more detailed and rich texture feature of target can be obtained by wavelet packet to image decomposition to compare with the wavelet decomposition. In the process of matching and recognition, the hierarchical recognition method is presented to improve the recognition speed and accuracy. The wavelet packet transformation is used to carry out the image decomposition. Through experiment results, the proposed recognition method has the high precision, fast speed, and its correct recognition rate is improved by an average 6.13% than that of existing recognition methods. These researches development in this paper can provide an important theoretical reference and practical significance to improve the real-time and accuracy on fuzzy target recognition.

App Controllable Intelligent Desk Lamp System

2015 ◽  
Vol 19 (2) ◽  
pp. 205-211
Author(s):  
Yu Ping Liao ◽  
◽  
Ruei Chang Lu ◽  
Pang Tzu Liu ◽  
Jing Xiang Cao ◽  
...  
Keyword(s):  
Image Processing ◽  
Motor Control ◽  
Control System ◽  
Vision System ◽  
Servo Motor ◽  
Verilog Hdl ◽  
Position Data ◽  
Processing Module ◽  
Motor Control System ◽  
Lamp System

In this paper, we propose a FPGA based intelligent desk lamp system with a camera, two servo motors and LEDs. The proposed lamp system can automatically trace a moving book with a red bookmark by pan and tilt control to provide sufficient illumination. Thus, the user can read book with enough light for eye caring. The architecture of the system includes a vision system and a servo-motor control system. The image processing module inside the system can obtain the book’s position data. According to the book’s position data, two servo motors automatically adjust the pan and tilt angles of the desk lamp. The adjustable ranges for pan and tilt angles are 40° and 30°, respectively. Additionally, an App is designed and allows the user to remotely control the lamp by using a smartphone. All the processing modules are implemented on Altera DE0-Nano kit with Cyclonetex® IV EP4CE22F17C6N FPGA with Verilog HDL.

scholarly journals Research on Multiperson Motion Capture System Combining Target Positioning and Inertial Attitude Sensing Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yifei Wang ◽  
Yongsheng Wang
Keyword(s):  
Real Time ◽  
Motion Capture ◽  
Inertial Sensors ◽  
Recognition Rate ◽  
Human Motion ◽  
Motion Capture System ◽  
Fusion Algorithm ◽  
Raw Data ◽  
Sensing Technology ◽  
Fusion Target

The purpose of this study is to solve the problems of multiple targets, poor accuracy, and inability to obtain displacement information in motion capture. Based on fusion target positioning and inertial attitude sensing technology, Unity3D is employed to create 3D scenes and 3D human body models to read real-time raw data from inertial sensors. Furthermore, a gesture fusion algorithm is used to process the raw data in real time to generate a quaternion, and a human motion capture system is designed based on inertial sensors for the complete movement information recording of the capture target. Results demonstrate that the developed system can accurately capture multiple moving targets and provide a higher recognition rate, reaching 75%∼100%. The maximum error of the system adopting the fusion target positioning algorithm is 10 cm, a reduction of 71.24% compared with that not using the fusion algorithm. The movements of different body parts are analyzed through example data. The recognition efficiency of “wave,” “crossover,” “pick things up,” “walk,” and “squat down” is as high as 100%. Hence, the proposed multiperson motion capture system that combines target positioning and inertial attitude sensing technology can provide better performance. The results are of great significance to promote the development of industries such as animation, medical care, games, and sports training.

A Hierarchical Target Recognition Method Based on Image Processing

2018 ◽  
pp. 494-510
Author(s):  
QingE Wu ◽  
Weidong Yang
Keyword(s):  
Image Processing ◽  
Feature Extraction ◽  
Target Recognition ◽  
Wavelet Packet ◽  
Recognition Rate ◽  
Image Decomposition ◽  
Extraction Process ◽  
Practical Significance ◽  
Recognition Method ◽  
Target Feature

In order to provide an accurate and rapid target recognition method for some military affairs, public security, finance and other departments, this paper studies firstly a variety of fuzzy signal, analyzes the uncertainties classification and their influence, eliminates fuzziness processing, presents some methods and algorithms for fuzzy signal processing, and compares with other methods on image processing. Moreover, this paper uses the wavelet packet analysis to carry out feature extraction of target for the first time, extracts the coefficient feature and energy feature of wavelet transformation, gives the matching and recognition methods, compares with the existing target recognition methods by experiment, and presents the hierarchical recognition method. In target feature extraction process, the more detailed and rich texture feature of target can be obtained by wavelet packet to image decomposition to compare with the wavelet decomposition. In the process of matching and recognition, the hierarchical recognition method is presented to improve the recognition speed and accuracy. The wavelet packet transformation is used to carry out the image decomposition. Through experiment results, the proposed recognition method has the high precision, fast speed, and its correct recognition rate is improved by an average 6.13% than that of existing recognition methods. These researches development in this paper can provide an important theoretical reference and practical significance to improve the real-time and accuracy on fuzzy target recognition.

Motion Capture of Fastening Operation Using Wiimotes for Ergonomic Analysis

2012 ◽  
Author(s):  
W. Zhu ◽  
C. P. Daphalapurkar ◽  
S. Chirayil Puthenveetil ◽  
M. C. Leu ◽  
X. F. Liu ◽  
...  
Keyword(s):  
Motion Capture ◽  
Vision System ◽  
Low Cost ◽  
Motion Capture System ◽  
Digital Human Modeling ◽  
Motion Data ◽  
Aircraft Fuselage ◽  
Modeling Software ◽  
Ergonomic Analysis ◽  
Digital Human

This paper presents an application of a Wii Remote (Wiimote) based, low-cost motion capture system for digital human simulation and ergonomic analysis of a fastening operation. The system includes a low-cost infrared (IR) based motion capture system developed using Wiimotes. A portable stereo vision system was used to capture the operator’s movements while performing a fastening operation during the assembly of an aircraft fuselage on the factory floor. IR LEDs mounted on the worker’s body served as markers. The captured motion data was used to generate a simulation of the operator’s arm movements and to perform ergonomic analysis with the help of digital human modeling software, Siemens Jack.

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