• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2C
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• pp.166-174
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• 2006

In this paper, a new stereo object tracking system using the disparity motion vector is proposed. In the proposed method, the time-sequential disparity motion vector can be estimated from the disparity vectors which are extracted from the sequence of the stereo input image pair and then using these disparity motion vectors, the area where the target object is located and its location coordinate are detected from the input stereo image. Being based on this location data of the target object, the pan/tilt embedded in the stereo camera system can be controlled and as a result, stereo tracking of the target object can be possible. From some experiments with the 2 frames of the stereo image pairs having 256$\times$256 pixels, it is shown that the proposed stereo tracking system can adaptively track the target object with a low error ratio of about 3.05$\%$ on average between the detected and actual location coordinates of the target object.

• Wind and Structures
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• v.14 no.6
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• pp.517-536
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• 2011

The assessment of wind-induced motion plays an important role in the development and design of the majority of today's structures that push the limits of engineering knowledge. A vital part of the design is the prediction of wind-induced tall building motion and the assessment of its effects on occupant comfort. Little of the research that has led to the development of the various international standards for occupant comfort criteria have considered the effects of the low-frequency motion on task performance and interference with building occupants' daily activities. It has only recently become more widely recognized that it is no longer reasonable to assume that the level of motion that a tall building undergoes in a windstorm will fall below an occupants' level of perception and little is known about how this motion perception could also impact on task performance. Experimental research was conducted to evaluate the performance of individuals engaged in a manual tracking task while subjected to low level vibration in the frequency range of 0.125 Hz-0.50 Hz. The investigations were carried out under narrow-band random vibration with accelerations ranging from 2 milli-g to 30 milli-g (where 1 milli-g = 0.0098 $m/s^2$) and included a control condition. The frequencies and accelerations simulated are representative of the level of motion expected to occur in a tall building (heights in the range of 100 m -350 m) once every few months to once every few years. Performance of the test subjects with and without vibration was determined for 15 separate test conditions and evaluated in terms of time taken to complete a task and accuracy per trial. Overall, the performance under the vibration conditions did not vary significantly from that of the control condition, nor was there a statistically significant degradation or improvement trend in performance ability as a function of increasing frequency or acceleration.

• Atmosphere
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• v.28 no.4
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• pp.443-455
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• 2018

Nowcasting algorithms using weather radar data are mostly based on extrapolating the radar echoes. We estimate the echo motion vectors that are used to extrapolate the echo properly. Therefore, understanding the general characteristics of these motion vectors is important to improve the performance of nowcasting. General characteristics of radar-based motions are analyzed for warm season precipitation over Jeju region. Three-year summer season data (June~August, 2011~2013) from two radars (GSN, SSP) in Jeju are used to obtain echo motion vectors that are retrieved by Variational Echo Tracking (VET) method which is widely used in nowcasting. The highest frequency occurs in precipitation motion toward east-northeast with the speed of $15{\sim}16m\;s^{-1}$ during the warm season. Precipitation system moves faster and eastward in June-July while it moves slower and northeastward in August. The maximum frequency of speed appears in $10{\sim}20m\;s^{-1}$ and $5{\sim}10m\;s^{-1}$ in June~July and August respectively while average speed is about $14{\sim}15m\;s^{-1}$ in June~July and $8m\;s^{-1}$ in August. In addition, the direction of precipitation motion is highly variable in time in August. The speed of motion in Lee side of the island is smaller than that of the windward side.

• ETRI Journal
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• v.38 no.2
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• pp.356-365
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• 2016

This research proposes a modified particle filter to increase the accuracy of vehicle tracking in a noisy and occluded medium. In our proposed method for vehicle tracking, the direction angle of a target vehicle is calculated. The angular difference between the motion direction of the target vehicle and each particle of the particle filter is observed. Particles are filtered and weighted depending on their angular distance to the motion direction. Those particles moving in a direction similar to that of the target vehicle are assigned larger weights; this, in turn, increases their probability in a given likelihood function (part of the process of estimation of a target's state parameters). The proposed method is compared against a condensation algorithm. Our results show that the proposed method improves the stability of a particle filter tracker and decreases the particle consumption.

• Journal of KIISE:Software and Applications
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• v.31 no.2
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• pp.173-181
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• 2004

In this paper, we propose a system for automatic moving object detection and tracking in sequence images acquired from a moving camera. The proposed algorithm consists of moving object detection and its tracking. Moving object can be detected by integration of BBME and DD method We segment the detected object using histogram back projection, match it using histogram intersection, extract and track it using XY-projection. Computer simulation results have shown that the proposed algorithm is reliable and can successfully detect and track a moving object on image sequences obtained by a moving camera.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.3
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• pp.320-331
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• 2019

In this paper, we propose a method of TMA(Target Motion Analysis) performance improvement using target elevation tracking and fusion in conformal array sonar. One of the most important characteristics of conformal array sonar is to detect a target elevation by a vertical beam. It is possible to get a target range to maximize advantages of the proposed TMA technology using this characteristic. And the proposed techniques include target tracking, target fusion, calculation of target range by multipath as well as TMA. A simulation study demonstrates the outstanding performance of proposed techniques.

• ETRI Journal
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• v.45 no.5
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• pp.836-846
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• 2023

Mobile robots are used in modern life; however, object recognition is still insufficient to realize robot navigation in crowded environments. Mobile robots must rapidly and accurately recognize the movements and shapes of pedestrians to navigate safely in pedestrian-rich spaces. This study proposes real-time, accurate, three-dimensional (3D) multi-pedestrian detection and tracking using a 3D light detection and ranging (LiDAR) point cloud in crowded environments. The pedestrian detection quickly segments a sparse 3D point cloud into individual pedestrians using a lightweight convolutional autoencoder and connected-component algorithm. The multi-pedestrian tracking identifies the same pedestrians considering motion and appearance cues in continuing frames. In addition, it estimates pedestrians' dynamic movements with various patterns by adaptively mixing heterogeneous motion models. We evaluate the computational speed and accuracy of each module using the KITTI dataset. We demonstrate that our integrated system, which rapidly and accurately recognizes pedestrian movement and appearance using a sparse 3D LiDAR, is applicable for robot navigation in crowded spaces.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.04a
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• pp.147-151
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• 1999

This paper extends and enhances the existing inverse kinematics technique using the concept of motion characteristic capturing. Motion characteristic capturing is not about measuring motion by tracking body points. Instead, it starts from pre-measured motion data, extracts the motion characteristics, and applies them in animating other bodies. The resulting motion resembles the originally measured one in spite of arbitrary dimensional differences between the bodies. Motion characteristics capturing is a new principle in kinematic motion generalization to process measurements and generate realistic animation of human being or other living creatures.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2821-2823
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• 2005

When we deal with the image data through camera lens, much works are necessary for removing image distortions and obtaining accurate informations from the raw data. However, the calibration process is very complicated and requires many trials and errors. In this paper, 3 new approach to image processing is presented by developing a H/W vision system with a tracking camera. Using motor control with encoders the proposed tracking method tells us exact displacements of a moving object. Therefore this method does not require any calibration process for pin cusion. Owing to the mobility one camera covers wide ranges and, by lowering its height, the camera also obtains high resolution of the image. We first introduce the structure of the motion analysis system. Then the construced vision system is investigated by some experiments.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.10a
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• pp.245-246
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• 2008

The goal of this study is to explore the possibility of KLT tracker for tracking the features between two images including rotation and shift. As a test site, Jangsu-Gun area of South Korea is selected and the images taken from UAV camera are used for analysis. The analysis was carried out using KLT tracker developed in a PC environment. The results of the experiment used two images with the large overlapping area are compared with the results of two images with the little overlapping area and rotation. Overall, the research indicates that the integrated features of littlerotation and motion images can significantly increase during the tracking process. But using KLT tracker for extracting and tracking features between images with large rotation and motion, the number of tracked features are decreased.