• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.135-135
• /
• 2001

In recent years there have been increasing interests in real-time object tracking with image information. Since image information is affected by illumination, this paper presents the real-time object tracking method based on neural networks that have robust characteristics under various illuminations. This paper proposes three steps to track the object and the fast tracking method. In the first step the object color is extracted using neural networks. In the second step we detect the object feature information based on invariant moment. Finally the object is tracked through a shape recognition using neural networks. To achieve the fast tracking performance, we have a global search for entire image and then have tracking the object through local search when the object is recognized.

• ETRI Journal
• /
• v.38 no.3
• /
• pp.435-443
• /
• 2016

In this paper, an efficient beam tracking algorithm for a regularized zero-forcing (RZF) approach in slowly fading multiple-input and single-output (MISO) broadcast channels is considered. By modifying an RZF equation, an RZF beam tracking algorithm is proposed using matrix perturbation theory. The proposed algorithm utilizes both beams from the previous time step and channel difference (between the previous and current time steps) to calculate the RZF beams. The tracking performance of the proposed algorithm is analyzed in terms of the mean square error (MSE) between a tracking approach and an exact recomputing approach, and in terms of the additional MSE caused by the beam tracking error at the receiver. Numerical results show that the proposed algorithm has almost the same performance as the exact recomputing approach in terms of the sum rate.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.5
• /
• pp.1711-1725
• /
• 2014

Multi-target tracking is the main purpose of many video surveillance applications. Recently, multi-target tracking based on the particle filter method has achieved robust results by using the data association process. However, this method requires many calculations and it is inadequate for real time applications, because the number of associations exponentially increases with the number of measurements and targets. In this paper, to reduce the computational cost of the data association process, we propose a novel multi-target tracking method that excludes particle samples in the overlapped predictive region between the target to track and marginal targets. Moreover, to resolve the occlusion problem, we define an occlusion mode with the normal dynamic mode. When the targets are occluded, the mode is switched to the occlusion mode and the samples are propagated by Gaussian noise without the sampling process of the particle filter. Experimental results demonstrate the robustness of the proposed multi-target tracking method even in occlusion.

• 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.

• Journal of the Korean Society of Radiology
• /
• v.15 no.2
• /
• pp.93-100
• /
• 2021

The purpose of this study is to find out the factors that affect the patient's exposure dose during the abdominal CT scan using the bolus tracking technique, and reducing the radiation exposure to the patient during the abdominal CT scan using the bolus tracking technique by adjusting the delay time according to the corresponding factor. The experiment was divided into two parts, and the first experiment was conducted with 300 patients There were 188 males and 112 females, and their average age was 58±12.18(19~85). In the second experiment, 150 subjects (100 males and 50 females) who were undergoing their follow-up examination among the first experiment subjects, and the difference in dose before and after was compared by applying the delay time according to the influencing factor. As a result of the first experiment, there was a relationship between the arrival time of the contrast media and the heart rate, and it was found that the arrival time decreased as the heart rate increased for both men and women. As a result of the second experiment, the average dose of CTDIvol and DLP before/after applying the delay time according to the heart rate decreased 4.98 mGy and 5.33 mGy·cm in the male group, and 3.54 mGy and 3.88 mGy·cm in the female group. By applying proper delay time according to the patient's heart rate during abdominal CT scan with the bolus tracking technique, the radiation exposure dose of the patient can be reduced.

• Proceedings of the KIEE Conference
• /
• 2008.10b
• /
• pp.333-334
• /
• 2008

A real-time face tracking is a broad topic, covering a large spectrum of technologies and applications. Briefly face tracking is a kind of tracing technique which follows human face in any directions. It needs some algorithms such as human face detection and motion controller to track face. Moreover, both processing time and calculation time are the most important factors that influence to drive tracking system. In this paper, two algorithms are used to find human face: earn-shift algorithm and face detection algorithm using OpenCV. Fuzzy controller is utilized to move pan-tilt camera system which can move four directions along to x-y axis.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.61 no.4
• /
• pp.639-642
• /
• 2012

Optical coherence tomography(OCT) can provide real-time and non-invasive subsurface imaging with ultra-high resolution of micrometer scale. However, conventional OCT systems generally have a limited imaging depth range within a depth of only 1-2 mm. To overcome the limitation, we have proposed an active surface tracking algorithm used in common-path Fourier-domain OCT system in order to extend the imaging depth range. The surface tracking algorithm based on the threshold and Savitzky-Golay filter of A-scan data was applied to real-time tracking. The algorithm has controlled a moving stage according to the sample's surface variance in real time. An OCT image obtained by the algorithm clearly show an extended imaging depth range. Consequently, the proposed algorithm demonstrated the potential for improving the conventional OCT systems with limitary depth range.

• Proceedings of the IEEK Conference
• /
• 2003.11a
• /
• pp.317-320
• /
• 2003

In this paper, we present real-time, accurate face region detection and tracking technique for an intelligent surveillance system. It is very important to obtain the high-resolution images, which enables accurate identification of an object-of-interest. Conventional surveillance or security systems, however, usually provide poor image quality because they use one or more fixed cameras and keep recording scenes without any clue. We implemented a real-time surveillance system that tracks a moving person using pan-tilt-zoom (PTZ) cameras. While tracking, the region-of-interest (ROI) can be obtained by using a low-pass filter and background subtraction. Color information in the ROI is updated to extract features for optimal tracking and zooming. The experiment with real human faces showed highly acceptable results in the sense of both accuracy and computational efficiency.

• Journal of the Korean Society for Precision Engineering
• /
• v.21 no.11
• /
• pp.83-90
• /
• 2004

In this paper we present a new real-time visual servoing unit for laparoscopic surgery This unit can automatically control laparoscope manipulator through visual tracking of laparoscopic surgical tool. For the tracking, we present two-stage adaptive CONDENSATION(conditional density propagation) algorithm to extract the accurate position of the surgical tool tip from a surgical image sequence in real-time. This algorithm can be adaptable to abrupt change of laparoscope illumination. For the control, we present virtual damper system to control a laparoscope manipulator safely and stably. This system causes the laparoscope to move under constraint of the virtual dampers which are linked to the four sides of image. The visual servoing unit operates the manipulator in real-time with locating the surgical tool in the center of image. The experimental results show that the proposed visual tracking algorithm is highly robust and the controlled manipulator can present stable view with safe.

• Fire Science and Engineering
• /
• v.21 no.3
• /
• pp.97-103
• /
• 2007

This experimental study showed the tracking characteristics of contaminated insulating materials. To analysis tracking characteristics, IEC 60112 was used. As the results of this study, the tracking characteristics of contaminated insulating materials showed as followings: (a) Comparative tracking index (CTI) of contaminated insulating material was lower than non-contaminated one. (b) First carbonized growth time and track growth time of contaminated insulating materials was faster than non-contaminated.