Implementation of a real-time moving object tracking system using visual servoing

Robotica ◽  
2003 ◽  
Vol 21 (6) ◽  
pp. 615-625 ◽  
Author(s):  
M-C. Tsai ◽  
K-Y. Chen ◽  
M-Y. Cheng ◽  
K.C. Lin
Keyword(s):  
Real Time ◽  
Visual Servoing ◽  
Tracking System ◽  
Moving Target ◽  
Tracking Accuracy ◽  
Security Systems ◽  
Detection Techniques ◽  
Control Scheme ◽  
High System ◽  
Automatically Tracking

Due to the increasing popularity of surveillance and security systems, the problem of automatically tracking a moving target by visual servoing has become a research topic deserving more investigation. Nonetheless, the success of tracking a moving target in real-time primarily depends on the performance of the motion detection techniques employed. This paper addresses visual tracking control of an unknown target that could be motional arbitrarily in the scene. A pan-tilt mechanism is used to gain the flexibility of tracking, and the so-called region-based matching method and motion energy method are modified and proposed in this study to detect a moving target based on the consecutive images acquired. A visual servo control scheme that adopts proportional control in the visual loop for reducing the servo lagging is proposed using output disturbance feedforward compensation. Experimental results show the superiority of the proposed method in achieving high system bandwidth and tracking accuracy.

scholarly journals A Study on Vision-Based Backstepping Control for a Target Tracking System

Actuators ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 105
Author(s):  
Thinh Huynh ◽  
Minh-Thien Tran ◽  
Dong-Hun Lee ◽  
Soumayya Chakir ◽  
Young-Bok Kim
Keyword(s):  
Control System ◽  
Visual Servoing ◽  
Tracking System ◽  
Experimental Studies ◽  
Imaging Geometry ◽  
Control Scheme ◽  
Decoupled Control ◽  
Control Configuration ◽  
A New Technique ◽  
Pointing Control

This paper proposes a new method to control the pose of a camera mounted on a two-axis gimbal system for visual servoing applications. In these applications, the camera should be stable while its line-of-sight points at a target located within the camera’s field of view. One of the most challenging aspects of these systems is the coupling in the gimbal kinematics as well as the imaging geometry. Such factors must be considered in the control system design process to achieve better control performances. The novelty of this study is that the couplings in both mechanism’s kinematics and imaging geometry are decoupled simultaneously by a new technique, so popular control methods can be easily implemented, and good tracking performances are obtained. The proposed control configuration includes a calculation of the gimbal’s desired motion taking into account the coupling influence, and a control law derived by the backstepping procedure. Simulation and experimental studies were conducted, and their results validate the efficiency of the proposed control system. Moreover, comparison studies are conducted between the proposed control scheme, the image-based pointing control, and the decoupled control. This proves the superiority of the proposed approach that requires fewer measurements and results in smoother transient responses.

Research on Underwater Target Tracking Based on Contour Detection

2011 ◽  
Vol 317-319 ◽  
pp. 890-896
Author(s):  
Ming Jun Zhang ◽  
Yuan Yuan Wan ◽  
Zhen Zhong Chu
Keyword(s):  
Prediction Model ◽  
Target Tracking ◽  
Tracking System ◽  
Contour Detection ◽  
Motion Prediction ◽  
Moving Target ◽  
Contour Extraction ◽  
Tracking Accuracy ◽  
Tracking Method ◽  
Underwater Target

The traditional centroid tracking method over-relies on the accuracy of segment, which easily lead to loss of underwater moving target. This paper presents an object tracking method based on circular contour extraction, combining region feature and contour feature. Through the correction to circle features, the problem of multiple solutions causing by Hough transform circle detection is avoided. A new motion prediction model is constructed to make up the deficiency that three-order motion prediction model has disadvantage of high dimension and large calculation. The predicted position of object centroid is updated and corrected by circle contour, forming prediction-measurement-updating closed-loop target tracking system. To reduce system processing time, on the premise of the tracking accuracy, a dynamic detection method based on target state prediction model is proposed. The results of contour extraction and underwater moving target experiments demonstrate the effectiveness of the proposed method.

Fast Tracking of Moving Target Combining SURF and Cluster Analysis

2013 ◽  
Vol 552 ◽  
pp. 542-547
Author(s):  
Ying Li ◽  
Jing Jiang Yu ◽  
Yue Gang Fu ◽  
Zheng Ping Xu ◽  
Xun Zhou
Keyword(s):  
Cluster Analysis ◽  
Real Time ◽  
Tracking System ◽  
Moving Target ◽  
Feature Points ◽  
Fast Tracking ◽  
Tracking Process ◽  
System Requirements ◽  
And Cluster Analysis ◽  
Environment Condition

In order to design a moving target fast tracking system with respect to a real-time and stable tracking process, especially when the shape of moving target or its environment condition changes, a new algorithm named SURF-KMs is proposed. SURF-KMs combines the advantages of SURF algorithm with a cluster analysis of K-means method. First, feature points are collected and then they generate the matching template vectors based on the SURF algorithm. Second, the feature points and the center of the target are estimated by using the K-means method to determine the target’s cluster scope and update the tracking window. Finally, a self-adapting updating strategy for matching template is also proposed in order to track moving target automatically. Experimental results indicate that SURF-KMs is mostly able to achieve a stable tracking while with the monitored target rotating, scale changing, and also the environment illumination glittering. Moreover, it can satisfy the system requirements of tracking stability, higher precision and anti-jamming.

The Software Design and Implementation of a Real-Time Automatic-Tracking System

2011 ◽  
Vol 383-390 ◽  
pp. 1595-1599
Author(s):  
Xin Yu Liu ◽  
Bo Gu
Keyword(s):  
Real Time ◽  
Software Design ◽  
Tracking System ◽  
Prediction Algorithm ◽  
Moving Target ◽  
Direction Discrimination ◽  
Target Field ◽  
Low Degree ◽  
Velocity Prediction

Aiming at the low degree and the poor real-time quality of the old monitoring system at present, this paper develops direction discrimination and velocity prediction algorithm in order to detect the parameters of moving object and then to control camera to track the abnormal moving target. Field test and operation prove that the system has a good tracking performance and stability.

scholarly journals Autonomous navigation of a magnetic colonoscope using force sensing and a heuristic search algorithm

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hao-En Huang ◽  
Sheng-Yang Yen ◽  
Chia-Feng Chu ◽  
Fat-Moon Suk ◽  
Gi-Shih Lien ◽  
...  
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Autonomous Navigation ◽  
Permanent Magnets ◽  
Search Algorithm ◽  
Tracking System ◽  
Training Model ◽  
Force Sensing ◽  
Tracking Accuracy ◽  
Surgical Safety

AbstractThis paper presents an autonomous navigation system for cost-effective magnetic-assisted colonoscopy, employing force-based sensors, an actuator, a proportional–integrator controller and a real-time heuristic searching method. The force sensing system uses load cells installed between the robotic arm and external permanent magnets to derive attractive force data as the basis for real-time surgical safety monitoring and tracking information to navigate the disposable magnetic colonoscope. The average tracking accuracy on magnetic field navigator (MFN) platform in x-axis and y-axis are 1.14 ± 0.59 mm and 1.61 ± 0.45 mm, respectively, presented in mean error ± standard deviation. The average detectable radius of the tracking system is 15 cm. Three simulations of path planning algorithms are presented and the learning real-time A* (LRTA*) algorithm with our proposed directional heuristic evaluation design has the best performance. It takes 75 steps to complete the traveling in unknown synthetic colon map. By integrating the force-based sensing technology and LRTA* path planning algorithm, the average time required to complete autonomous navigation of a highly realistic colonoscopy training model on the MFN platform is 15 min 38 s and the intubation rate is 83.33%. All autonomous navigation experiments are completed without intervention by the operator.

Intelligent real-time pressure tracking system using a novel hybrid control scheme

2017 ◽  
Vol 40 (13) ◽  
pp. 3744-3759 ◽  
Author(s):  
Zhonglin Lin ◽  
Tianhong Zhang ◽  
Qi Xie
Keyword(s):  
Real Time ◽  
Pulse Width Modulation ◽  
Time Pressure ◽  
Hybrid Control ◽  
Tracking System ◽  
Control Scheme ◽  
Field Programmable ◽  
Switching Method ◽  
Original Approach ◽  
Hybrid Control Scheme

In this paper, a novel hybrid control scheme is proposed to improve the control performance in a real-time pressure tracking system using fast on-off solenoid valves. In this novel hybrid control scheme, an original approach named Time Interlaced Modulation (TIM) is developed to replace the traditional Pulse Width Modulation (PWM) approach. Besides using TIM, a new switching method which is referred as seven possible control modes is designed to ensure the proper switching states of the valves. Moreover, a controller with field programmable gate array (FPGA) is chosen to guarantee the real-time implementation of the control algorithm. All the simulations and experimental results implemented on FPGA verify the feasibility of the hybrid control scheme.

Optimizing Design of Real-Time Spatial Moving Target Tracking System

2011 ◽  
Vol 328-330 ◽  
pp. 2234-2237
Author(s):  
Dong Sheng Liang ◽  
Zhao Hui Liu ◽  
Wen Liu
Keyword(s):  
Real Time ◽  
Video Processing ◽  
Tracking System ◽  
Processing System ◽  
Video Tracking ◽  
Image Resolution ◽  
Frame Rate ◽  
Moving Target ◽  
Detection And Tracking ◽  
Operation Speed

Achieving the detection and tracking of moving targets has been widely applied in all fields of today's society. Because of the shortcomings of traditional video tracking system, this paper proposes a novel method for designing video processing system based on hardware design of FPGA and DSP, and moving target in video can be detected and tracked by this system. In this system, DSP as the core of the system, it mainly completes the processing algorithms of video and image data, FPGA as a coprocessor, responsible for the completion of the processing of external data and logic. The hardware structure, link configuration, program code and other aspects of system are optimized. Finally, through the experiment, the input frame rate of video is 40frames/s, and the image resolution is 512pixels × 512pixels, median 16bites quantitative image sequence, the system can complete the relevant real-time detection and tracking algorithm and extract targets position of image sequences correctly. The results show that the advantage is that this system has powerful operation speed, real time, high accuracy and stability.

Adaptive Interacting Multiple Model Unscented Particle Filter Tracking Algorithm

2012 ◽  
Vol 190-191 ◽  
pp. 906-910 ◽  
Author(s):  
Hong Jiang Liu
Keyword(s):  
Probability Density Function ◽  
Particle Filter ◽  
Probability Density ◽  
Real Time ◽  
Density Function ◽  
Tracking System ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Tracking Accuracy ◽  
Unscented Particle Filter

In order to study the tracking problem of maneuvering image sequence target in complex environment with multi-sensor array, the adaptive interacting multiple model unscented particle filter algorithm based on measured residual is proposed. The motion array tracking system dynamic model is established, and initialized probability density function also is defined based on unscented transformation, after that, the measured covariance and state covariance are online adjusted by measured residual and adaptive factor, then the self-adapting capability of filter gain and the real-time capability of posterior probability density function are improved. Finally, the simulation results between different algorithms show the validity and superiority of the presented algorithm in tracking accuracy, stability and real-time capability.

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