• Journal of Magnetics
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• v.19 no.2
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• pp.174-180
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• 2014

In this paper, a new and simple method is proposed to quickly estimate the induced electric field in the human child exposed to a 100 kHz-10 MHz magnetic field, for the sake of electromagnetic field (EMF) safety assessment. The quasi-static finite-difference time-domain (FDTD) method is used to calculate the induced electric fields in high resolution 3D human child models with various body size parameters, in order to derive the correction factor for the estimation equation. The calculations are repeated for various frequencies and incident angles of the magnetic field. Based on these calculation results, a new and simple estimation equation for the 99th percentile value of the body electric field is derived that depends on the body size parameters, and the incident magnetic field. The estimation errors were equal to or less than 5.1%, for all cases considered.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2328-2344
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• 2022

2D human pose estimation still faces difficulty in low-resolution images. Most existing top-down approaches scale up the target human bonding box images to the large size and insert the scaled image into the network. Due to up-sampling, artifacts occur in the low-resolution target images, and the degraded images adversely affect the accurate estimation of the joint positions. To address this issue, we propose a multi-resolution input feature fusion network for human pose estimation. Specifically, the bounding box image of the target human is rescaled to multiple input images of various sizes, and the features extracted from the multiple images are fused in the network. Moreover, we introduce a guiding channel which induces the multi-resolution input features to alternatively affect the network according to the resolution of the target image. We conduct experiments on MS COCO dataset which is a representative dataset for 2D human pose estimation, where our method achieves superior performance compared to the strong baseline HRNet and the previous state-of-the-art methods.

• Proceedings of the KOSOMBE Conference
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• v.1992 no.11
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• pp.58-62
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• 1992

Hybrid optical-electronic procedures are introduced for the automated estimation of cell parameters (e.g., size, size variation, and shape). Two different optical Fourier analysis procedures are applied to high contrast cell boundary patterns obtained from specular micrographs of the endothelial layer. In one case, a large number of cell patterns are illuminated to extract average cell size information. Once the average cell size information has been obtained, individual cells are illuminated to extract shape information.

• Journal of the Korea Society of Computer and Information
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• v.23 no.8
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• pp.9-16
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• 2018

In this paper, a kidnapping detection scheme in which human pose estimation is used to classify accurately between kidnapping cases and normal ones is proposed. To estimate human poses from input video, human's 10 joint information is extracted by OpenPose library. In addition to the features which are used in the previous study to represent the size change rates and the regularities of human activities, the human pose estimation features which are computed from the location of detected human's joints are used as the features to distinguish kidnapping situations from the normal accompanying ones. A frame-based kidnapping detection scheme is generated according to the selection of J48 decision tree model from the comparison of several representative classification models. When a video has more frames of kidnapping situation than the threshold ratio after two people meet in the video, the proposed scheme detects and notifies the occurrence of kidnapping event. To check the feasibility of the proposed scheme, the detection accuracy of our newly proposed scheme is compared with that of the previous scheme. According to the experiment results, the proposed scheme could detect kidnapping situations more 4.73% correctly than the previous scheme.

• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.597-604
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• 2004

Accurate software cost estimation is essential to both developers and customers. Most of the cost estimating models based on the size measure methods, such as LOC and FP, are obtained through size estimation. The accuracy of size estimation directly influences the accuracy of cost estimation. As a result, the overall structure of regression-based cost models applies the power function based on software size. Many growth phenomenon in nature such as the growth in living organism, performance of technology, and learning capability of human show an S-shaped curve. This paper proposes a model which estimates the developing effort by using the growth curve. The presented model assumes that the relation cost and size follows the growth curve. The appropriateness of the growth curve model based on Function Point, Full-Function Point and Use-Case Point, which are the general methods in estimating the software size have been confirmed. The proposed growth curve model shows similar performance with power function model. In conclusion, the growth curve model can be applied in the estimation of the software cost.

• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.252-260
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• 2016

The performance of human detection system is affected by camera location and view angle. In 2D image acquired from such camera settings, humans are displayed in different sizes. Detecting all the humans with diverse sizes poses a difficulty in realizing a real-time system. However, if the size of a human in an image can be predicted, the processing time of human detection would be greatly reduced. In this paper, we propose a method that estimates human size by constructing an indoor scene in 3D space. Since the human has constant size everywhere in 3D space, it is possible to estimate accurate human size in 2D image by projecting 3D human into the image space. Experimental results validate that a human size can be predicted from the proposed method and that machine-learning based detection methods can yield the reduction of the processing time.

• Journal of Sensor Science and Technology
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• v.29 no.6
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• pp.440-446
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• 2020

A well-known difficulty in attitude estimation based on inertial measurement unit (IMU) signals is the occurrence of external acceleration under dynamic motion conditions, as the acceleration significantly degrades the estimation accuracy. Lee et al. (2012) designed a Kalman filter (KF) that could effectively deal with the acceleration issue. Ahmed and Tahir (2017) modified this method by adjusting the acceleration-related covariance matrix because they considered covariance modeling as a pivotal factor in the estimation accuracy. This study investigates the effects of covariance modeling on estimation accuracy in an IMU-based attitude estimation KF. The method proposed by Ahmed and Tahir can be divided into two: one uses the covariance including only diagonal components and the other uses the covariance including both diagonal and off-diagonal components. This paper compares these three methods with respect to the motion condition and the window size, which is required for the methods by Ahmed and Tahir. Experimental results showed that the method proposed by Lee et al. performed the best among the three methods under relatively slow motion conditions, whereas the modified method using the diagonal covariance with a high window size performed the best under relatively fast motion conditions.

• The Korean Journal of Legal Medicine
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• v.42 no.4
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• pp.141-145
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• 2018

There have been many radiographic studies on age estimation that evaluate reduction in size of dental pulp cavity with secondary dentin formation. The Paewinsky method reported high accuracy in estimating ages by measuring the width of the pulp cavity in panoramic radiographs. The aim of this study was to evaluate the application of the Paewinsky method to digital periapical radiographs. This study was conducted on 103 cases that reported to the Section of Human Identification of the National Forensic Service. The age was calculated by applying the Paewinsky method that measures the root and pulp canal width at three points in a tooth. The estimation results were compared with those calculated by the Johanson method. When the Paewinsky models were applied to digital periapical radiographs, the errors were significantly greater as compared to the original study. The errors of the maxillary second premolar and mandibular lateral incisor were greater than those of the maxillary central incisor, lateral incisor, mandibular canine, and first premolar. Furthermore, errors of the age estimation models in level C were greater than those in levels A and B. This study could be a reference for the application of the Paewinsky method to digital periapical radiographs.

• Communications of the Korean Mathematical Society
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• v.16 no.3
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• pp.459-485
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• 2001

The aim of EIT (electrical impedance tomography) system is to image cross-section conductivity distribution of a human body by means of both generating and sensing electrodes attached on to the surface of the body, where currents are injected and voltages are measured. EIT has been suffered from the severe ill-posedness which is caused by the inherent low sensitivity of boundary measurements to any changes of internal tissue conductivity values. With a limited set of current-to-voltage data, figuring out full structure of the conductivity distribution could be extremely difficult at present time, so it could be worthwhile to extract some necessary partial information of the internal conductivity. We try to extract some key patterns of current-to-voltage data that furnish some core information on the conductivity distribution such s location and size. This overview provides our recent observation on the location search and the size estimation.

• Journal of the Ergonomics Society of Korea
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• v.24 no.2
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• pp.51-56
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• 2005

Human perceptional speed is different from its real speed. There is lack of research that the perceptional speed is different from real speed in 2-dimension, because most research of speed perception has concentrated on points and lines. This research investigates the effects of object size on speed perception. In this research, we used 2-D circular objects of the different size, 0.9, 1.8 and $3.6^{\circ}$. The objects moved 9.0, 13.5 and $18.0^{\circ}$ with three different speeds, 6.0, 9.0 and $18.0^{\circ}$/s. Six participants were exposed to the environment with standard scene(size: $1.8^{\circ}$, speed: $9.0^{\circ}$/s and travel distance: $13.5^{\circ}$). After the first scene, another scene in which the object had changed to different sizes, speeds and distances, was shown to the participants. A magnitude estimation method was used to construct a scale of the perceived speed level. The relationship between the perceived and the actual speed level was explained by Stevens's power law that the value was 0.978 with the exponent of 0.992. The size of object had an effect on the speed perception but travel distance was not. The perceptional speed of bigger object was lower than of smaller object. It showed that the degrees of perceptional speed decreased as size of object increased.