• Journal of the Korea Institute of Military Science and Technology
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• v.5 no.2
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• pp.169-184
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• 2002

In order to extract bearing information from the directional sensors of DIFAR(directional frequency analysis and recording) that is a kind of passive sonobuoy, the cardioid beamforming algorithm applicable to DIFAR system was studied in the frequency domain. the algorithm uses narrow-band signals propagated though the media from the acoustic sources such as ship machineries. The proposed algorithm is expected to give signal to noise ratio of 6dB when it uses the maximum response axis(MRA) among the Cardioid beams. The estimated bearings agree very well with those from GPS data. Assuming the bearings from GPS data to be real values, the estimation errors are analyzed statistically. The histogram of estimation errors in each frequency have Gaussian shape, the mean and standard deviation dropping in the ranges -1.1~$6.7^{\circ}$ and 13.3~$43.6^{\circ}$, respectively. Estimation errors are caused by SMR degradation due to propagation loss between the source and receiver, daily fluctuating geo-magnetic fields, and non-stationary background noises. If multiple DIFAR systems are employed, in addition to bearing, range information could be estimated and finally localization or tracking of a target is possible.

• Journal of computational fluids engineering
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• v.22 no.1
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• pp.37-42
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• 2017

Infrared signals are frequently used to detect objects exposed to wide variety of environmental conditions. Detection by infrared signature is accomplished by distinguishing objects by using the IR radiant contrast between objects and the background. There are several methods of estimating the IR radiant contrast. The inverse distance weighting method, which is one of the IR radiant contrast estimation method using the effect of distance from objects, is known to be an effective way to analyze radiant contrast for complex backgrounds. However this method has a disadvantage of requiring a long calculation time. In this study we propose a statistical method of estimating the IR radiant contrast by using randomly selected pixels of arbitrary number among background pixels to reduce calculation time. Some measured IR images in MWIR and LWIR regions are used to test the applicability of the method proposed and we found that the proposed method is very effective in determining the IR radiant contrast showing very rapid estimation with minar accuracy loss.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.3
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• pp.315-327
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• 2017

In this paper, we present a method for estimating of position and velocity of a moving target by using the range and the bearing measurements from multiple sensors of aiming unit. In many cases, conventional low cost gyro sensor and a portable laser range finder(LRF) degrade the accuracy of estimation. To enhance these problems, we propose two methods. The first is background image tracking and the other is principal component analysis (PCA). The background tracking is used to assist the low cost gyro censor. And the PCA is used to cope with the problems of a portable LRF. In this paper, we prove that our method is robust with respect to low-frequency, biased and noisy inputs. We also present a comparison between our method and the extended Kalman filter(EKF).

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.5
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• pp.31-42
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• 2019

With the recent development of deep learning technology, remarkable achievements have been made in many research areas of computer vision. Deep learning has also made dramatic improvement in two-dimensional or three-dimensional human pose estimation based on a single image, and many researchers have been expanding the scope of this problem. The human pose estimation is one of the most important research fields because there are various applications, especially it is a key factor in understanding the behavior, state, and intention of people in image or video analysis. Based on this background, this paper surveys research trends in estimating human poses based on a single image. Because there are various research results for robust and accurate human pose estimation, this paper introduces them in two separated subsections: 2D human pose estimation and 3D human pose estimation. Moreover, this paper summarizes famous data sets used in this field and introduces various studies which utilize human poses to solve their own problem.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.12
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• pp.517-524
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• 2022

Human pose estimation is a method of estimating a posture by extracting a human joint key point. When occlusion occurs, the joint key point extraction performance is lowered because the human joint is covered. The occlusion phenomenon is largely divided into three types of actions: self-contained, covered by other objects, and covered by background. In this paper, we propose an effective posture estimation method using a masking phenomenon enhancement technique. Although the posture estimation method has been continuously studied, research on the occlusion phenomenon of the posture estimation method is relatively insufficient. To solve this problem, the author proposes a data augmentation technique that intentionally masks human joints. The experimental results in this paper show that the intentional use of the blocking phenomenon enhancement technique is strong against the blocking phenomenon and the performance is increased.

• Journal of Radiation Protection and Research
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• v.45 no.2
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• pp.53-68
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• 2020

Background: International organizations such as the World Health Organization (WHO) and the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) reported public exposure doses due to radionuclides released in the Fukushima nuclear accident a few years after the event. However, the reported doses were generally overestimated due to conservative assumptions such as a longer stay in deliberate areas designated for evacuation than the actual stay. After these reports had been published, more realistic dose values were reported by Japanese scientists. Materials and Methods: The present paper reviews those reports, including the most recently published articles; and summarizes estimated effective doses (external and internal) and issues related to their estimation. Results and Discussion: External dose estimation can be categorized as taking two approaches-estimation from ambient dose rate and peoples' behavior patterns-and measurements using personal dosimeters. The former approach was useful for estimating external doses in an early stage after the accident. The first 4-month doses were less than 2 mSv for most (94%) study subjects. Later on, individual doses came to be monitored by personal dosimeter measurements. On the basis of these measurements, the estimated median annual external dose was reported to be < 1 mSv in 2011 for 22 municipalities of Fukushima Prefecture. Internal dose estimation also can be categorized as taking two approaches: estimation from whole-body counting and estimation from monitoring of environmental samples such as radioactivity concentrations in food and drinking water. According to results by the former approach, committed effective dose due to ¹³⁴Cs and ¹³⁷Cs could be less than 0.1 mSv for most residents including those from evacuated areas. Conclusion: Realistic doses estimated by Japanese scientists indicated that the doses reported by WHO and UNSCEAR were generally overestimated. Average values for the first-year effective doses for residents in two affected areas (Namie Town and Iitate Village) were not likely to reach 10 mSv, the lower end of the doses estimated by WHO.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.2
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• pp.149-154
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• 2014

Detection performance of fire detection in the outdoor depends on weather conditions, the shadow by the movement of the sun, or illumination changes. In this paper, a smoke detection in conjunction with a robust background estimate algorithm to environment change in the outdoor in daytime is proposed. Gaussian Mixture Model (GMM) is applied as background estimation, and also, statistical characteristics of smoke is applied to detect the smoke for separated candidate region. Through the experiments with input videos obtained from a various weather conditions, the proposed algorithms were useful to detect smoke in the outdoor.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.789-790
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• 2008

In this paper, we introduce the multi-target-based auto surveillance algorithm. Multi-target-based surveillance system detects intrusion objects in the specified areas. The proposed algorithm can divide into two parts: i) background generation, ii) object extraction. In this paper, one of the optical flow equation methods for estimation of gradient method used to generate the background [2]. In addition, the objects and back- ground video images that are continually entering the differential extraction.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.951-952
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• 2008

This paper proposes a new method for image composition which estimates the rotation angle of human hand and uses the reserved image in real-time camera images. First, we capture a background image and extract a interesting region by background subtraction. Next, we estimate the skin region from the interesting region and calculate the rotation angle of estimated skin region using PCA(Principal Components Analysis). Finally, we composite the reserved image for the calculated rotation angle in camera images. The proposed method can be applied to control the 3D avatar for marker-less augmented reality.

• Publications of The Korean Astronomical Society
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• v.20 no.1 s.24
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• pp.49-53
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• 2005

We are often faced with the task of having to estimate the amplitude of a source signal in the presence of a background. In the simplest case, the background can be taken as being flat, and of unknown magnitude B, and the source signal of interest assumed to be the amplitude A of a peak of known shape and position. We present a robust method to find the most probable values of A and B by applying the one-dimensional Newton-Raphson method. In the derivation of the formula, we adopted the Bayesian statistics and assmumed Poisson distribution so that the results could be applied to the analysis of very weak signals, as observed in FIMS (Far-ultraviolet IMaging Spectrogaph).