• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.4
• /
• pp.1066-1079
• /
• 2023

Multi-target tracking based on the detector is a very hot and important research topic in target tracking. It mainly includes two closely related processes, namely target detection and target tracking. Where target detection is responsible for detecting the exact position of the target, while target tracking monitors the temporal and spatial changes of the target. With the improvement of the detector, the tracking performance has reached a new level. The problem that always exists in the research of target tracking is the problem that occurs again after the target is occluded during tracking. Based on this question, this paper proposes a DeepSORT model based on SIFT features to improve ship tracking. Unlike previous feature extraction networks, SIFT algorithm does not require the characteristics of pre-training learning objectives and can be used in ship tracking quickly. At the same time, we improve and test the matching method of our model to find a balance between tracking accuracy and tracking speed. Experiments show that the model can get more ideal results.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1997.04a
• /
• pp.25-29
• /
• 1997

In this thesis, we construct the microrobot succor system and navigate the real-time path planning and visual tracking of each robot. The system consists robots, vision system and a host computer. Because the robots are free-ranging mobile robot, it is needed to make and gallow the path. The path is planned and controlled by a host computer, ie. Supervisory control system. In path planning, we suggest a cost function which consists of three terms. One is the smoothness of the path, another is the total distance or time, and the last one is to avoid obstacles. To minimize the cost function, we choose the parametric cubic spline and update the coefficients in real time. We perform the simulation for the path planing and obstacle avoidance and real experiment for visual tracking

• Journal of the Semiconductor & Display Technology
• /
• v.10 no.3
• /
• pp.21-28
• /
• 2011

In recent years, owing to the development of the image processing technology, the research to build control system using a vision sensor is stimulated. However, a random time delay must be considered, because it works of a various time to get a result of an image processing in the system. It can be seen as an obstacle factor to a control of visual tracking in real system. In this paper, implementing two vision controllers each, first one is made up PID controller and the second one is consisted of a Smith Predictor, the possibility was shown to overcome a problem of a random time delay in a visual tracking system. A number of simulations and experiments were done to show the validity of this study.

• Bulletin of the Korean Chemical Society
• /
• v.22 no.5
• /
• pp.455-462
• /
• 2001

The time-dependent tracking inversion method is studied to extract the potential energy surface of the electronic excited state in the photodissociation of triatomic molecules. Based on the relay of the regularized inversion procedure and time-dependent wave packet propagation, the algorithm extracts the underlying potential energy surface piece by piece by tracking the time-dependent data, which can be synthesized from Raman excitation profiles. We have demonstrated the algorithm to extract the potential energy surface of electronic excited state for NO2 molecule where the wave packet split on a saddle-shaped surface. Finally, we describe the merits of the time-dependent tracking inversion method compared with the time-independent inversion method and discussed several extensions of the algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.10 no.1
• /
• pp.191-196
• /
• 2006

This paper presents the moving object tracking method using vision system. In order to track object in real time, the image of moving object have to be located the origin of the image coordinate axes. Accordingly, Fuzzy Control System is investigated for tracking the moving object, which control the camera module with Pan/Tilt mechanism. Hereafter, so the this system is applied to mobile robot, we design and implement image processing board for vision system. Also fuzzy controller is implemented to the StrongArm board. Finally, the proposed fuzzy controller is useful for the real-time moving object tracking system by experiment.

• Proceedings of the IEEK Conference
• /
• 2004.08c
• /
• pp.729-734
• /
• 2004

The e-Logistics means the virtual business activity and service architecture among the logistics companies based on the Internet technology. The management of vehicles' location in most conventional vehicle tracking system has some critical defects when it deals with data which are continuously changed. It means the conventional vehicle tracking system based on the conventional database is unable eventually to cope with the environment that should manage the frequently changed location of vehicles. The important things in the evaluation of the vehicle tracking system is to determine the threshold of cost of database ,update period and communication period between vehicles and the system. In other words, the difference between the reallocation of vehicle and the data in database can evaluate the overall performance of vehicle tracking systems. Most of the previous works considers only the information that is valid at the current time, and is hard to manage efficiently the past and future information. To overcome this problem, the efforts on moving objects management system(MOMS) and uncertainty processing have been started from a few years ago. In this paper, we propose an uncertainty processing model and system implementation of moving object that tracks the location of the vehicles. We adopted both linear-interpolation method and trigonometric function to chase up the location of vehicles for the past time as well as future time, respectively. We also explain the comprehensive examples of MOMS and uncertainty processing in parcel application that is one of major application of e-Logistics domain.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.6
• /
• pp.2483-2503
• /
• 2016

Traffic congestion is a severe problem in many modern cities around the world. Real-time and accurate traffic congestion identification can provide the advanced traffic management systems with a reliable basis to take measurements. The most used data sources for traffic congestion are loop detector, GPS data, and video surveillance. Video based traffic monitoring systems have gained much attention due to their enormous advantages, such as low cost, flexibility to redesign the system and providing a rich information source for human understanding. In general, most existing video based systems for monitoring road traffic rely on stationary cameras and multiple vehicle tracking method. However, most commonly used multiple vehicle tracking methods are lack of effective track initiation schemes. Based on the motion of the vehicle usually obeys constant velocity model, a novel vehicle recognition method is proposed. The state of recognized vehicle is sent to the GM-PHD filter as birth target. In this way, we relieve the insensitive of GM-PHD filter for new entering vehicle. Combining with the advanced vehicle detection and data association techniques, this multiple vehicle tracking method is used to identify traffic congestion. It can be implemented in real-time with high accuracy and robustness. The advantages of our proposed method are validated on four real traffic data.

• The Journal of Korea Robotics Society
• /
• v.8 no.4
• /
• pp.266-272
• /
• 2013

Facial feature extraction and tracking are essential steps in human-robot-interaction (HRI) field such as face recognition, gaze estimation, and emotion recognition. Active shape model (ASM) is one of the successful generative models that extract the facial features. However, applying only ASM is not adequate for modeling a face in actual applications, because positions of facial features are unstably extracted due to limitation of the number of iterations in the ASM fitting algorithm. The unaccurate positions of facial features decrease the performance of the emotion recognition. In this paper, we propose real-time facial feature extraction and tracking framework using ASM and LK optical flow for emotion recognition. LK optical flow is desirable to estimate time-varying geometric parameters in sequential face images. In addition, we introduce a straightforward method to avoid tracking failure caused by partial occlusions that can be a serious problem for tracking based algorithm. Emotion recognition experiments with k-NN and SVM classifier shows over 95% classification accuracy for three emotions: "joy", "anger", and "disgust".

• Fire Science and Engineering
• /
• v.22 no.5
• /
• pp.67-71
• /
• 2008

This experimental study showed the tracking characteristics of contaminated insulating materials of RCD. Electrolytes is made by IEC(International Electrotechnical Commission) 60589, NaCl added to deionized water as each 0.1 wt%. The used test equipment is application to KS(Korean Industrial Standard) C IEC 60112. The used samples is RCD(Residual Current Device) of tree companies. It is investigated carbonic electric conductive pass growth time and tracking growth form that contaminated insulators materials of RCD. As a result, carbonic electric conductive pass growth time and tracking growth form was different each companies. Track growth time of contaminated insulating materials was faster than non-contaminated.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.39 no.9
• /
• pp.883-888
• /
• 2011

The UAV tracking antenna system based on GPS has a characteristic of update of position information which can occurs a position error. To reduce the position error, UAV tracking antenna system separates period of GPS update-rate and predicts the position of UAV using divided time points. These process improves the tracking performance of UAV. To predict the position of UAV by divided time points, we used a linear kalman filter based on the velocity and acceleration. Using this system, we measured velocity and acceleration according to the change of position. Finally, we can predict the change of position on divided time points.