• The KIPS Transactions:PartB
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• v.17B no.5
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• pp.355-362
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• 2010

Face tracking is to estimate the motion of a non-rigid face together with a rigid head in 3D, and plays important roles in higher levels such as face/facial expression/emotion recognition. In this paper, we propose an AAM-based face tracking algorithm. AAM has been widely used to segment and track deformable objects, but there are still many difficulties. Particularly, it often tends to diverge or converge into local minima when a target object is self-occluded, partially or completely occluded. To address this problem, we utilize the scale invariant feature transform (SIFT). SIFT is an effective method for self and partial occlusion because it is able to find correspondence between feature points under partial loss. And it enables an AAM to continue to track without re-initialization in complete occlusions thanks to the good performance of global matching. We also register and use the SIFT features extracted from multi-view face images during tracking to effectively track a face across large pose changes. Our proposed algorithm is validated by comparing other algorithms under the above 3 kinds of occlusions.

• Journal of KIISE
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• v.43 no.3
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• pp.353-361
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• 2016

During image-guided radiation treatment of lung cancer patients, it is necessary to track the tumor motion because it can change during treatment as a consequence of respiratory motion and cardiac motion. In this paper, we propose a method for tracking the motion of the lung tumors based on the three-dimensional image information from planning 4D MDCT and treatment 4D CBCT images. First, to effectively track the tumor motion during treatment, the global motion of the tumor is estimated based on a tumor-specific motion model obtained from planning 4D MDCT images. Second, to increase the accuracy of the tumor motion tracking, the local motion of the tumor is estimated based on the structural information of the tumor from 4D CBCT images. To evaluate the performance of the proposed method, we estimated the tracking results of proposed method using digital phantom. The results show that the tumor localization error of local motion estimation is reduced by 45% as compared with that of global motion estimation.

• Journal of Advanced Navigation Technology
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• v.20 no.5
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• pp.490-495
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• 2016

In the present study, a microstrip-fed monopole antenna is proposed for wireless local area network (WLAN) operations which cover dual band of 2.4 GHz (2.4 ~ 2.484 GHz) and 5 GHz (5.15 ~ 5.825 GHz). In order to obtain its compact structure and good omnidirectional radiation patterns, a modified inverted L-shaped slot separated from ground for impedance matching in 5 GHz band is etched on 2.4 GHz printed monopole antenna. The proposed antenna is designed and fabricated on a FR4 substrate with dielectric constant 4.3, thickness of 1.6 mm, and size of $30{\times}45mm^2$. The measured impedance bandwidths (${\mid}S_{11}{\mid}{\leq}-10dB$) of fabricated antenna are 270 MHz (2.22 ~ 2.48 GHz) in 2.4 GHz band and 890 MHz (5.08 ~ 5.97 GHz) in 5 GHz band respectively. In particular, high gain of more than about 4 dBi and good omnidirectional radiation patterns have been observed over the entire frequency band of interest.

• Journal of Korea Multimedia Society
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• v.6 no.3
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• pp.508-517
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• 2003

This paper presents perceptual model with a stochastic multiresolution characteristic that can be applied with watermark embedding in the biorthogonal wavelet domain. The perceptual model with adaptive watermarking algorithm embeds at the texture and edge region for more strongly embedded watermark by the SSQ. The watermark embedding is based on the computation of a NVF that has local image properties. This method uses non- stationary Gaussian and stationary Generalized Gaussian models because watermark has noise properties. The particularities of embedding in the stationary GG model use shape parameter and variance of each subband regions in multiresolution. To estimate the shape parameter, we use a moment matching method. Non-stationary Gaussian model uses the local mean and variance of each subband. The experiment results of simulation were found to be excellent invisibility and robustness. Experiments of such distortion are executed by Stirmark 3.1 benchmark test.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.1972-1978
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• 2010

AAM(Active Appearance Model) is one of the most effective ways to detect deformable 2D objects and is a kind of mathematical optimization methods. The cost function is a convex function because it is a least-square function, but the search space is not convex space so it is not guaranteed that a local minimum is the optimal solution. That is, if the initial value does not depart from around the global minimum, it converges to a local minimum, so it is difficult to detect face contour correctly. In this study, an AAM-based face tracking algorithm is proposed, which is robust to various lighting conditions and backgrounds. Eye detection is performed using SIFT and Genetic algorithm, the information of eye are used for AAM's initial matching information. Through experiments, it is verified that the proposed AAM-based face tracking method is more robust with respect to pose and background of face than the conventional basic AAM-based face tracking method.

• The Journal of the Acoustical Society of Korea
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• v.22 no.7
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• pp.562-572
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• 2003

A matched-target model inversion method was developed for a passive sonar to estimate the position of moving targets. Based on the well known matched-field processing in underwater acoustics, the method finds target position by matching the measured target directions and frequencies with the corresponding values of the proposed target model. For the efficient and accurate estimations, the parameter searching was accomplished using a hybrid optimizing method, which first starts with a global optimization such as generic algorithm or simulated annealing then applies a local optimization of a simple down hill algorithm. The suggested method was testified using simulations for three different moving scenarios. The simulation results showed that the method is robust in convergence, even under the situation of over 5 times standard deviation of Gaussian distribution of measured error, and is practical in calculation time as well.

• Journal of the Korea Convergence Society
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• v.11 no.11
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• pp.345-352
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• 2020

Under "Emergency Doctor Security Act of 2007", Japanese government focuses on relocating doctors in medically underserved areas and matching supply and demand of manpower in order to resolve the ubiquity of specific treatment departments. Particularly, there are two alternatives to secure the number of local physicians and avoid the regional shortage of doctors in the short term. Firstly, the government attracts existing physicians to the region. Secondly, the government increases the capability of regional clinical training system to prevent the influx of doctors to the larger cities. Also, it seeks solutions from various perspectives, such as cultivating manpower to work in vulnerable areas through the regional frame system and autonomous medical college. This study introduces the case of Japan as a benchmark and suggests that policymakers should focus on the recent conflict between the government and the medical consultation. More specifically, this study provides policy implications on the alternative measures for securing the manpower of regional doctors.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.1
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• pp.128-135
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• 2009

Techniques for tracking the same region of physical space with the temporal sequences of images by matching the contours of constant phase show robust and stable performance in relative to the tracking techniques using or assuming the constant intensity. Using this property, we describe an algorithm for obtaining the robust motion parameters caused by the global camera motion. First, we obtain the optical flow based on the phase of spacially filtered sequential images on the region in a direction orthogonal to orientation of each component of gabor filter bank. And then, we apply the least squares method to the optical flow to determine the affine motion parameters. We demonstrate hat proposed method can be applied to the vision based pointing device which estimate its motion using the image including the display device which cause lighting condition varieties and noise.

• Journal of Advanced Navigation Technology
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• v.16 no.2
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• pp.386-393
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• 2012

In this paper, we propose an efficient multi-object recognition and tracking scheme based on interest points of objects and their feature descriptors. To do that, we first define a set of object types of interest and collect their sample images. For sample images, we detect interest points and construct their feature descriptors using SURF. Next, we perform a statistical analysis of the local features to select representative points among them. Intuitively, the representative points of an object are the interest points that best characterize the object. in addition, we make the movement vectors of the interest points based on matching between their SURF descriptors and track the object using these vectors. Since our scheme treats all the objects independently, it can recognize and track multiple objects simultaneously. Through the experiments, we show that our proposed scheme can achieve reasonable performance.

• Journal of Biomedical Engineering Research
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• v.25 no.2
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• pp.111-117
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• 2004

Most of digital subtraction methods in dental radiography are based on registration using manual landmarks. We have developed an automatic registration method without using the manual selection of landmarks. By restricting a geometrical matching of images to a region of interest (ROl), we compare the cross-correlation coefficient only between the ROIs. The affine or perspective transform parameters satisfying maximum of cross-correlation between the local regions are searched iteratively by a fast searching strategy. The parameters are searched on the 1/4 scale image coarsely and then, the fine registration is performed on the original scale image. The developed method can match the images corrupted by Gaussian noise with the same accuracy for the images without any transform simulation. The registration accuracy of the perspective method shows a 17% improvement over the manual method. The application of the developed method to radiography of dental implants provides an automatic noise robust registration with high accuracy in almost real time.