• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.2
• /
• pp.710-726
• /
• 2018

This paper presents an extended particle filter to increase the accuracy and decrease the computation load of vehicle tracking. Particle filter has been the subject of extensive interest in video-based tracking which is capable of solving nonlinear and non-Gaussian problems. However, there still exist problems such as preventing unnecessary particle consumption, reducing the computational burden, and increasing the accuracy. We aim to increase the accuracy without an increase in computation load. In proposed method, we calculate the direction angle of the target vehicle. The angular difference between the direction of the target vehicle and each particle of the particle filter is observed. Particles are filtered and weighted, based on their angular difference. Particles with angular difference greater than a threshold is eliminated and the remaining are stored with greater weights in order to increase their probability for state estimation. Threshold value is very critical for performance. Thus, instead of having a constant threshold value, proposed algorithm updates it online. The first advantage of our algorithm is that it prevents the system from failures caused by insufficient amount of particles. Second advantage is to reduce the risk of using unnecessary number of particles in tracking which causes computation load. Proposed algorithm is compared against camshift, direction-based particle filter and condensation algorithms. Results show that the proposed algorithm outperforms the other methods in terms of accuracy, tracking duration and particle consumption.

• Transactions on Electrical and Electronic Materials
• /
• v.14 no.4
• /
• pp.187-192
• /
• 2013

Because of the importance of small target detection in infrared images, many studies have been carried out in this area. Using a Kalman filter and mean shift algorithm, this study proposes an algorithm to track multiple small moving targets even in cases of target disappearance and appearance in serial infrared images in an environment with many noises. Difference images, which highlight the background images estimated with a background estimation filter from the original images, have a relatively very bright value, which becomes a candidate target area. Multiple target tracking consists of a Kalman filter section (target position prediction) and candidate target classification section (target selection). The system removes error detection from the detection results of candidate targets in still images and associates targets in serial images. The final target detection locations were revised with the mean shift algorithm to have comparatively low tracking location errors and allow for continuous tracking with standard model updating. In the experiment with actual marine infrared serial images, the proposed system was compared with the Kalman filter method and mean shift algorithm. As a result, the proposed system recorded the lowest tracking location errors and ensured stable tracking with no tracking location diffusion.

• Proceedings of the KIEE Conference
• /
• 2009.04b
• /
• pp.219-221
• /
• 2009

This paper analyzes efficiency of photovoltaic(PV) tracking system using solar location algorithm(SLA). Solar location tracking system is needed for efficiently and intensively using PV system independent of environmental condition. PV tracking system of program method is presented a high tracking accuracy without the wrong operating in rapidly changed insolation by the clouds and atmospheric condition. Therefore, this paper analyzes efficiency of PV system using SLA for more correct position tracking of solar. Also, controlled altitude angle and azimuth angle by applied algorithm is compared with data of korea astronomy observatory. And this paper analyzes the tracking error and proves the validity of applied algorithm.

• International Journal of Control, Automation, and Systems
• /
• v.4 no.2
• /
• pp.236-246
• /
• 2006

Motion tracking and object segmentation are the most fundamental and critical problems in vision tasks such as motion analysis. An active contour model, snake, was developed as a useful segmenting and tracking tool for rigid or non-rigid objects. In this paper, the development of new snake model called 'adaptive color snake model (ACSM)' for segmentation and tracking is introduced. The simple operation makes the algorithm runs in real-time. For robust tracking, the condensation algorithm was adopted to control the parameters of ACSM. The effectiveness of the ACSM is verified by appropriate simulations and experiments.

• Journal of Institute of Control, Robotics and Systems
• /
• v.15 no.6
• /
• pp.649-654
• /
• 2009

In this paper, an frequency tracking algorithm for weak signal tracking is proposed. The proposed frequency tracking algorithm uses a FMS (Fast Minus Slow) discriminator for frequency error estimation. This frequency tracking algorithm shows good frequency estimation performance under weak signal condition and is a computationally efficient for embedded software GNSS receiver. The software GNSS receiver implementing the proposed weak signal tracking algorithms could track GPS signal down to - 159dBm signal strength in the signal generator test and real GPS signal under dense urban condition.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.60 no.9
• /
• pp.1721-1726
• /
• 2011

Recently, interest in renewable energy is increased due to exhaustion of fossil fuel and environmental pollution all over the world, therefore the solar power generation using solar energy is many researched. The solar power generation is required solar tracking control and high concentration solar thermal collector because generation performance is depended on concentrator efficiency. This paper proposes high efficiency solar power generation with two-axis tracking control using dish-type solar thermal collector that has excellent thermal collector performance and tracking algorithm that can be accurately tracked solar position. This paper proves validity through analysis with accuracy of tracking algorithm and generating efficiency.

• Journal of Institute of Control, Robotics and Systems
• /
• v.15 no.8
• /
• pp.839-844
• /
• 2009

In this paper, a real-time eye tracking method using fast face detection is proposed. Most of the current eye tracking systems have operational limitations due to sensors, complicated backgrounds, and uneven lighting condition. It also suffers from slow response time which is not proper for a real-time application. The tracking performance is low under complicated background and uneven lighting condition. The proposed algorithm detects face region from acquired image using elliptic Hough transform followed by eye detection within the detected face region using Haar-like features. In order to reduce the computation time in tracking eyes, the algorithm predicts next frame search region from the information obtained in the current frame. Experiments through simulation show good performance of the proposed method under various environments.

• The Journal of Korea Robotics Society
• /
• v.2 no.2
• /
• pp.129-136
• /
• 2007

This paper introduces a position-based robust visual servoing method which is developed for operation of a human-like robot with two arms. The proposed visual servoing method utilizes SIFT algorithm for object detection and CAMSHIFT algorithm for object tracking. While the conventional CAMSHIFT has been used mainly for object tracking in a 2D image plane, we extend its usage for object tracking in 3D space, by combining the results of CAMSHIFT for two image plane of a stereo camera. This approach shows a robust and dependable result. Once the robot's task is defined based on the extracted 3D information, the robot is commanded to carry out the task. We conduct several position-based visual servoing tasks and compare performances under different conditions. The results show that the proposed visual tracking algorithm is simple but very effective for position-based visual servoing.

• Journal of The Korean Astronomical Society
• /
• v.34 no.4
• /
• pp.237-241
• /
• 2001

Our goal is to present a simple volume-of-fluid type interface-tracking algorithm to compressible two-phase flow in two space dimensions. The algorithm uses a uniform underlying Cartesian grid with some cells cut by the tracked interfaces into two subcells. A volume-moving procedure that consists of two basic steps: (1) the update of volume fractions in each grid cell at the end of the time step, and (2) the reconstruction of interfaces from discrete set of volume fractions, is employed to follow the dynamical behavior of the interface motion. As in the previous work with a surface-tracking procedure for general front tracking (LeVeque & Shyue 1995, 1996), a high resolution finite volume method is then applied on the resulting slightly nonuniform grid to update all the cell values, while the stability of the method is maintained by using a large time step wave propagation approach even in the presence of small cells and the use of a time step with respect to the uniform grid cells. A sample preliminary numerical result for an underwater explosion problem is shown to demonstrate the feasibility of the algorithm for practical problems.

• Proceedings of the KSME Conference
• /
• 2001.06b
• /
• pp.307-312
• /
• 2001

In this paper, we proposed the object-tracking algorithm that recognizes and estimates the any shaped and size objects using vision system. For the extraction of the object from the background of the acquired images, spatio-temporal filter and signature parsing algorithm are used. Specially, for the solution of correspondence problem of the multiple objects tracking, we compute snake energy and position information of the target objects. Through the real-time tracking experiment, we verified the effectiveness of the suggested tracking algorithm.