• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.2
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• pp.143-148
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• 2014

Particle filter algorithm has been proven very successful for non-linear and non-Gaussian estimation problem and thus it has been widely used for object tracking for video signals. If the object moves significantly, particle filter needs very large number of particles to track object and this results high computational cost. In this paper, modified particle filter by adopting motion vector is proposed for tracking vehicle in low frame rate(LPR) video input, which the object moving significantly and randomly between consecutive frames. In the proposed algorithm, motion vector is applied in selection and observe step. The experimental result shows that the proposed particle filter can track vehicle successfully in the case when previous one fails. And it also shows the propose method increases the precision of tracking.

• Journal of IKEEE
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• v.6 no.1 s.10
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• pp.54-64
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• 2002

In this paper, we propose the algorithm for segmenting the moving speaker and tracking its movement in the video conference image. For real time processing, we simplify the algorithm which is processed in the order of the segmenting and the tracking step. In the segmenting step, the speaker object is segmented from the image by using both the motion information obtained from the difference method and the illuminance information of image. The reference mask image is created from segmented speaker object. In the tracking step, the moving speaker is tracked by using simple block matching algorithm of which computation time is reduced by discarding the blocks which are classified into the unuseful blocks. In the simulation, we can get the good result of segmenting and tracking the moving speaker by applying the proposed algorithm to several test images.

• Smart Structures and Systems
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• v.26 no.4
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• pp.419-433
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• 2020

Investigation of structural integrity has been a critical issue in the field of civil engineering for years. Visual inspection is one of the most available methods to explore deteriorative components in structures. Still, this method is not applicable to invisible damage of structures. Alternatively, system identification methods are capable of tracking modal properties of structures over time. The deviation of these dynamic properties can serve as indicators to access structural integrity. In this study, a modal tracking technique using frequency-domain system identification from seismic responses of structures is proposed. The method first segments the measured signals into overlapped sequential portions and then establishes multiple Hankel matrices. Each Hankel matrix is then converted to the frequency domain, and a temporal-average frequency-domain Hankel matrix can be calculated. This study also proposes the frequency band selection that can divide the frequency-domain Hankel matrix into several portions in accordance with referenced natural frequencies. Once these referenced natural frequencies are unavailable, the first few right singular vectors by the singular value decomposition can offer these references. Finally, the frequency-domain stochastic subspace identification tracks the natural frequencies and mode shapes of structures through quick stabilization diagrams. To evaluate performance of the proposed method, a numerical study is carried out. Moreover, the long-term monitoring strong motion records at a specific site are exploited to assess the tracking performance. As seen in results, the proposed method is capable of tracking modal properties through seismic responses of structures.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.11
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• pp.43-51
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• 2021

A robust tracking controller design was developed for a rotary motion control system. The friction force versus the angular velocity was measured and modeled as a combination of linear and nonlinear components. By adding a model-based friction compensator to a nominal proportional-integral-derivative controller, it was possible to build a simulated control system model that agreed well with the experimental results. A zero-phase error tracking controller was selected as the feedforward tracking controller and implemented based on the estimated closed-loop transfer function. To provide robustness against external disturbances and modeling uncertainties, a disturbance observer was added in the position feedback loop. The performance improvement of the overall tracking controller structure was verified through simulations and experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8C
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• pp.1175-1183
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• 2004

This paper propose a method to trace a moving object based on the information directly obtained from MPEG-2 compressed video stream without decoding process. In the proposed method, the motion flow is constructed from the motion vectors involved in compressed video and then we calculate the amount of pan, tilt, zoom associated with camera operations using generalized Hough transform. The local object motion can be extracted from the motion flow after the compensation with the parameters related to the global camera motion. The moving object is designated initially by a user via bounding box. After then automatic tracking is performed based on the mean-shift algorithm of the motion flows of the object. The proposed method can improve the computation speed because the information is directly obtained from the MPEG-2 compressed video, but the object boundary is limited by blocks rather than pixels.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.11
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• pp.79-88
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• 1999

In this paper we address the tracking method which tracks only target object in image sequence including moving object. We use a contour tracking algorithm based on intensity and motion boundaries. The motion of the moving object contour in the image is assumed to be well describable by an affine motion model with a translation, a change in scale and a rotation. The moving object contour is represented by B-spline, the position and motion of which is estimated along the image sequence. we use pattern recognition to identify target object. In order to use linear Kalman Filters we decompose the estimation process into two filters. One is estimating the affine motion parameters and the other the shape of moving object contour. In some experiments with dial plate we show that this method enables us to obtain the robust motion estimates and tracking trajectories even in case of including obstructive object.

• Progress in Medical Physics
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• v.10 no.3
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• pp.115-123
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• 1999

The two dimensional echocardiography is widely used to evaluate regional wall motion abnormality, because of its abilities to depict left ventricular wall motion. A number of researches have been processed for evaluation and quantitative analysis of left ventricular wall motion functions. In this paper, we proposed an algorithm which detects automatically and analyze quantitatively endocardial wall motion during systole. The echocardiograms were obtained in the short-axis views in normal subjects. Automated edge detection and endocardial contour tracking algorithm was applied to each frames, quantitative analysis based on segmentation was performed, pre-defined color overlays superimposed on the gray scale images, and the images was animated. The proposed algorithm provided automated, quantitative diagnosis of regional wall motion abnormality.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.7
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• pp.2579-2585
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• 2010

This paper proposes a dynamic human pose tracking method using motion-based search strategy from an image sequence obtained from a monocular camera. The proposed method compares the image features between 3D human model projections and real input images. The method repeats the process until predefined criteria and then estimates 3D human pose that generates the best match. When searching for the best matching configuration with respect to the input image, the search region is determined from the estimated 2D image motion and then search is performed randomly for the body configuration conducted within that search region. As the 2D image motion is highly constrained, this significantly reduces the dimensionality of the feasible space. This strategy have two advantages: the motion estimation leads to an efficient allocation of the search space, and the pose estimation method is adaptive to various kinds of motion.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.23-34
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• 2004

In this paper we propose a feature point tracking algorithm using optical flow under non-prior taming active feature model (NPT-AFM). The proposed algorithm mainly focuses on analysis non-rigid objects[1], and provides real-time, robust tracking by NPT-AFM. NPT-AFM algorithm can be divided into two steps: (i) localization of an object-of-interest and (ii) prediction and correction of the object position by utilizing the inter-frame information. The localization step was realized by using a modified Shi-Tomasi's feature tracking algoriam[2] after motion-based segmentation. In the prediction-correction step, given feature points are continuously tracked by using optical flow method[3] and if a feature point cannot be properly tracked, temporal and spatial prediction schemes can be employed for that point until it becomes uncovered again. Feature points inside an object are estimated instead of its shape boundary, and are updated an element of the training set for AFH Experimental results, show that the proposed NPT-AFM-based algerian can robustly track non-rigid objects in real-time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.2C
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• pp.16-24
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• 2005

In this paper, we proposed a face tracking algorithm for a viewpoint adaptive multi-view synthesis system. The original scene captured by a depth camera contains a texture image and 8 bit gray-scale depth map. From this original image, multi-view images can be synthesized which correspond to viewer's position by using geometrical transformation such as a rotation and a translation. The proposed face tracking technique gives a motion parallax cue by different viewpoints and view angles. In the proposed algorithm, tracking of viewer's dominant face initially established from camera by using statistical characteristics of face colors and deformable templates is done. As a result, we can provide motion parallax cue by detecting viewer's dominant face area and tracking it even under a heterogeneous background and can successfully display the synthesized sequences.