• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.510-513
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• 1986

In recent years the Kalman filter(extended Kalman filter) have been applied to a wide variety of tracking moving targets, because of its properties. For such a reason, in this paper we attempt to study on adaptive filter algorithms which estimate unknown bias maneuvering inputs.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.802-812
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• 2019

With the rapid development in the field of unmanned aerial vehicles(UAVs) and drones, higher request to development of a surveillance system for a drone is putting forward. Since surveillance systems with fixed cameras have a limited range, a development of surveillance systems with a moving camera applicable to PTZ(Pan-Tilt-Zoom) cameras is required. Selecting the features for object plays a critical role in tracking, and the object has to be represented by their shapes or appearances. Considering these conditions, in this paper, an object tracking method with optical flow is introduced to track a tiny drone with a moving camera. In addition, a tracking method combined with kalman filter is proposed to track continuously even when tracking is failed. Experiments are tested on sequences which have a target from the minimal 12 pixels to the maximal 56337 pixels, the proposed method achieves average precision of 175% improvement. Also, experimental results show the proposed method tracks a target which has a size of 12pixels.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3196-3210
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• 2014

This paper presents a novel video metrology approach based on robust tracking. From videos acquired by an uncalibrated stationary camera, the foreground likelihood map is obtained by using the Codebook background modeling algorithm, and the multiple moving objects are tracked by a combined tracking algorithm. Then, we compute vanishing line of the ground plane and the vertical vanishing point of the scene, and extract the head feature points and the feet feature points in each frame of video sequences. Finally, we apply a single view mensuration algorithm to each of the frames to obtain height measurements and fuse the multi-frame measurements using RANSAC algorithm. Compared with other popular methods, our proposed algorithm does not require calibrating the camera, and can track the multiple moving objects when occlusion occurs. Therefore, it reduces the complexity of calculation and improves the accuracy of measurement simultaneously. The experimental results demonstrate that our method is effective and robust to occlusion.

• Journal of KIISE:Software and Applications
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• v.34 no.10
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• pp.937-944
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• 2007

In this paper, we propose multiple human tracking with an moving stereo camera. The tracking process is based on mean shift algorithm which is using color information of the target. Color based tracking approach is invariant to translation and rotation of the target but, it has several problems. Because of mean shift uses color distribution, it is sensitive to color distribution of background and targets. In order to solve this problem, we combine color and depth information of target. Also, we build human body part model to handle occlusions and we have created adaptive box scale. As a result, the proposed method is simple and efficient to track multiple humans in real time.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.4
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• pp.359-365
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• 2001

In this paper, we propose the design methodology of target tracking system using fuzzy basis function expansion(FBFE) based on virus evolutionary genetic algorithm (VEGA). In general, the objective of target tracking is to estimate the future trajectory of the target based on the past position of the target obtained from the sensor. In the conventional and mathematical nonlinear filtering method such as extended Kalman filter(EKF), the performance of the system may be deteriorated in highly nonlinear situation. To resolve these problems of nonlinear filtering technique, by appling artificial intelligent technique to the tracking control of moving targets, we combine the advantages of both traditional and intelligent control technique. In the proposed method, after composing training datum from the parameters of extended Kalman filter, by combining FDFE, which has the strong ability for the approximation, with VEGA, which prevent GA from converging prematurely in the case of lack of genetic diversity of population, and by idenLifying the parameters and rule numbers of fuzzy basis function simultaneously, we can reduce the tracking error of EKF. Finally, the proposed method is applied to three dimensional tracking problem, and the simulation results shows that the tracking performance is improved by the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.198-204
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• 2012

Tracking and recognition of robots are required for the cooperation task of robots in various environments. In the paper, a tracking control system of moving robot using stereo image processing, code-book model and fuzzy controller is proposed. First, foreground and background images are separated by using code-book model method. A candidate region is selected based on the color information in the separated foreground image and real distance of the robot is estimated from matching process of depth image that is acquired through stereo image processing. The open and close processing of image are applied and labeling according to the size of mobile robot is used to recognize the moving robot effectively. A fuzzy tracking controller using distance information and mobile information by stereo image processing is designed for effective tracking according to the movement velocity of the target robot. The proposed fuzzy tracking control method is verified through tracking experiments of mobile robots with stereo camera.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.34D no.7
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• pp.88-96
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• 1997

As the need of automatized system has been increased recently together with the development of industrial and military technologies, the adaptive real-time target detection technologies that can be embedded on vehicles, planes, ships, robots and so on, are hgihly demanded. Accordingly, this paper proposes a novel approach to detect and segment the moving targets using the binary phase extraction joint transform correlator (BPEJTC), the advanced image subtraction filter and convex hull processing. The BPEJTC which was used as a target detection unit mainly for target tracking compensating the camera movement. The target region has been detected by processing the successful three frames using the advanced image subtraction filter, and has become more accurate by applying the developed convex hull filter. As shown by some experimental results, it is expected that the proposed approaches for compensation of the camera movement and segmentationof of target region, can be used for th emissile guiddance, aero surveillance, automatic inspectin system as well as the target detection unit of automatic target recognition system that request adaptive real-time processing.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.3_1spc
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• pp.607-614
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• 2013

This paper proposes a robot driving system and sensor implementation for use with an education robot. This robot has multiple functions and was designed so that children could use it with interest and ease. The robot recognizes the location of a user and follows that user at a specific distance when the robot and user communicate with each other. In this work, the robot was designed and manufactured to evaluate its performance. In addition, an embedded board was installed with the purpose of communicating with a smart phone, and a camera mounted on the robot allowed it to monitor the environment. To allow the robot to follow a moving user, a set of sensors combined with an RF module and ultrasonic sensors were adopted to measure the distance between the user and the robot. With the help of this ultrasonic sensors arrangement, the location of the user couldbe identified in all directions, which allowed the robot to follow the moving user at the desired distance. Experiments were carried out to see how well the user's location could be recognized and to investigate how accurately the robot trackedthe user, which eventually yielded a satisfactory performance.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.335-337
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• 1994

The correlation tracker developed by John M. Fitts in 1979 is the most complex to mechanize but provides the best tracking performance in a low SNR condition. Correlation tracker would rewove the requirements for optimizing threshold and has no need to know information about the target. But if the displacement of the target is large, the tracking error of the correlation tracker tends to diverge. In this paper, we suggest a precision image tracking algorithm which improves the tracking performance via iterative application of the matched filter estimation algorithm.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.1
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• pp.66-74
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• 2012

The virtual target signal generator was developed to verify the shipborne tracking radar performance. It was used to DRFM(Digital RF Memory) method to generate the virtual moving targets. The target signal includes Doppler shift and RCS according to the target motion. And the signal generator can make jamming signal and clutter to test shipborne radar performance at real environmental condition. This paper described the functional diagram and the hardware configuration items to meet the test requirements for the tracking radar. And it showed the critical design points for the sub-systems. The signal generator which was developed in this paper shared the operational information of the radar with the radar command and control part. To test the frequency agility of the radar, it had the local oscillator which could do high speed frequency switching according to radar information. By communicating between the signal generator and the radar command and control part, the local oscillator of signal generator could be controlled every pulse. It reduced the instantaneous bandwidth of signal generator and minimized the spurious. So it lowered the probability of generating wrong targets.