• The KIPS Transactions:PartB
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• v.18B no.1
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• pp.21-28
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• 2011

A 3D face shape derived from 2D images may be useful in many applications, such as face recognition, face synthesis and human computer interaction. To do this, we develop a fast 3D Active Appearance Model (3D-AAM) method using depth estimation. The training images include specific 3D face poses which are extremely different from one another. The landmark's depth information of landmarks is estimated from the training image sequence by using the approximated Jacobian matrix. It is added at the test phase to deal with the 3D pose variations of the input face. Our experimental results show that the proposed method can efficiently fit the face shape, including the variations of facial expressions and 3D pose variations, better than the typical AAM, and can estimate accurate 3D face shape from images.

• Journal of Korea Multimedia Society
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• v.12 no.8
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• pp.1089-1098
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• 2009

Recently, many researches of making more comfortable input device based on gaze detection technology have been performed in human computer interface. Previous researches were performed on the computer environment with a large sized monitor. With recent increase of using mobile device, the necessities of interfacing by gaze detection on mobile environment were also increased. In this paper, we research about the gaze detection method by using UMPC (Ultra-Mobile PC) and an embedded camera of UMPC based on face and facial feature detection by AAM (Active Appearance Model). This paper has following three originalities. First, different from previous research, we propose a method for tracking user's gaze position in mobile device which has a small sized screen. Second, in order to detect facial feature points, we use AAM. Third, gaze detection accuracy is not degraded according to Z distance based on the normalization of input features by using the features which are obtained in an initial user calibration stage. Experimental results showed that gaze detection error was 1.77 degrees and it was reduced by mouse dragging based on the additional facial movement.

• Journal of Advanced Navigation Technology
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• v.17 no.5
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• pp.552-559
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• 2013

According to the recent increase of mobile commerce, the researches on electronic voucher payment based on NFC are lively made. However, most researches focus on the payment method using electronic vouchers, and so there is none for tracking circulation history of an electronic voucher. To address this problem, this paper proposes the method to store circulation information of an electronic voucher. The proposed method applies Object Memory Model (OMM) to an electronic voucher. When an electronic voucher is issued, transferred to other person, and used in payment, related information is stored at the object momory of an electronic voucher. So, our proposed object memory has three types of blocks, on which each information for issue, transfer, and payment of an electronic voucher is stored. We can retrieve and analyze the circulation history of an electronic voucher using this information. In the future, we will implement the proposed an electronic voucher and propose the method to analyze circulation information.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.1
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• pp.27-34
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• 2013

Background subtraction is one of the key techniques for automatic video content analysis, especially in the tasks of visual detection and tracking of moving object. In this paper, we present a new sample-based technique for background extraction that provides background image as well as background model. To handle both high-frequency and low-frequency events at the same time, multiple interval background models are adopted. The main innovation concerns the use of a confidence factor to select the best model from the multiple interval background models. To our knowledge, it is the first time that a confidence factor is used for merging several background models in the field of background extraction. Experimental results revealed that our approach based on multiple interval sampling works well in complicated situations containing various speed moving objects with environmental changes.

• Nuclear Engineering and Technology
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• v.47 no.7
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• pp.838-848
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• 2015

One of the most important operations in nuclear power plants is load following, in which an imbalance of axial power distribution induces xenon oscillations. These oscillations must be maintained within acceptable limits otherwise the nuclear power plant could become unstable. Therefore, bounded xenon oscillation is considered to be a constraint for the load following operation. In this paper, the design of a sliding mode control (SMC), which is a robust nonlinear controller, is presented.SMCis ameansto control pressurized water nuclear reactor (PWR) power for the load following operation problem in a way that ensures xenon oscillations are kept bounded within acceptable limits. The proposed controller uses constant axial offset (AO) strategy to ensure xenon oscillations remain bounded. The constant AO is a robust state constraint for the load following problem. The reactor core is simulated based on the two-point nuclear reactor model with a three delayed neutron groups. The stability analysis is given by means of the Lyapunov approach, thus the control system is guaranteed to be stable within a large range. The employed method is easy to implement in practical applications and moreover, the SMC exhibits the desired dynamic properties during the entire output-tracking process independent of perturbations. Simulation results are presented to demonstrate the effectiveness of the proposed controller in terms of performance, robustness, and stability. Results show that the proposed controller for the load following operation is so effective that the xenon oscillations are kept bounded in the given region.

• Journal of Platform Technology
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• v.8 no.3
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• pp.3-9
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• 2020

As the need for sharing for research purposes in the medical field increases, the use of a Common Data Model (CDM) is increasing. However, when sharing CDM data, there are some problems in that access control and personal information in the data are not protected. In this paper, in order to solve this problem, access to CDM data is controlled by using an encryption method in a blockchain network, and information of CDM data is recorded to enable tracking. In addition, IPFS was used to share a large amount of CDM data, and Celery was used to automate the sharing process. In other words, we propose a multi-channel automation system in which the information required for CDM data sharing is shared by a trust-based technology, a distributed file system, and a message queue for automation. This aims to solve the problem of access control and personal information protection in the data that occur in the process of sharing CDM data.

• The Journal of Korean Institute of Information Technology
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• v.17 no.9
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• pp.91-97
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• 2019

When a radar tracks the warhead of a ballistic missile, decoys of a ballistic missile put a heavy burden on the radar resource management tracking the targets. To reduce this burden, it is necessary to be able to separate the signal of the warhead from the received dynamic radar cross section (RCS) signal on the radar. In this paper, we propose the method of separating the dynamic RCS of each target from the received signal by the Hough transform which extracts straight lines from the image. The micro motion of the targets was implemented using a 3D CAD model of the warhead and decoys. Then, we calculated the dynamic RCS from the 3D CAD model having micromotion and verified the performance by applying the proposed algorithm. Simulation results show that the proposed method can separate the signals of the warhead and decoys at the signal-to-noise ratio (SNR) of 10dB.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.439-445
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• 2021

Low-cost, ultra-high-speed cameras, made possible by the development of image sensors and small displays, can be very useful in image processing and pattern recognition. This paper introduces an algorithm that corrects irregular lighting from a high-speed image that is continuously input with a slight time interval, and which then obtains an exposed skin color region that is the area of interest in a person from the corrected image. In this study, the non-uniform lighting effect from a received high-speed image is first corrected using a frame blending technique. Then, the region of interest is robustly obtained from the input high-speed color image by applying an elliptical skin color distribution model generated from iterative learning in advance. Experimental results show that the approach presented in this paper corrects illumination in various types of color images, and then accurately acquires the region of interest. The algorithm proposed in this study is expected to be useful in various types of practical applications related to image recognition, such as face recognition and tracking, lighting correction, and video indexing and retrieval.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.423-432
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• 2022

This paper addresses the safety concern that the SOH of batteries in electric vehicles decreases sharply when drivers change or their driving patterns change. Such a change can overload the battery, reduce the battery life, and induce safety issues. This paper aims to present the SOH as the changes on a dashboard of an electric vehicle in real-time in response to user pattern changes. As part of the training process I used battery data among the datasets provided by NASA, and built models incorporating linear regression and ARIMA, and predicted new battery data that contained user changes based on previously trained models. Therefore, as a result of the prediction, the linear regression is better at predicting some changes in SOH based on the user's pattern change if we have more battery datasets with a wide range of independent values. The ARIMA model can be used if we only have battery datasets with SOH data.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.63-70
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• 2023

Due to the spread of high-definition black boxes and the introduction of mobile applications such as 'Smart Citizens Report' and 'Safety Report', the number of public interest reports for violations of Traffic Law has increased rapidly, resulting in shortage of police personnel to handle them. In this paper, we describe the development of a system that can automatically detect lane violations which account for the largest proportion of public interest reporting videos for violations of traffic laws, using deep learning algorithms. In this study, a method for recognizing a vehicle and a solid line object using a YOLO model and a Lanenet model, a method for tracking an object individually using a deep sort algorithm, and a method for detecting lane change violations by recognizing the overlapping range of a vehicle object's bounding box and a solid line object are described. Using this system, it is expected that the shortage of police personnel in charge will be resolved.