• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2645-2648
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• 2003

In this paper, real-time and reconfiguable hardware filter for face recognition is proposed and implemented on FPGA chip using verilog-HDL. In general, face recognition is considerably difficult because it is influenced by noises or the variation of illumination. Some of the commonly used filters such s histogram equalization filter, contrast stretching filter for image enhancement and illumination compensation filter are proposed for realizing more effective illumination compensation. The filter proposed in this paper was designed and verified by debugging and simulating on hardware. Experimental results show that the proposed filter system can generate selective set of real-time reconfiguable hardware filters suitable for face recognition in various situation.

• Journal of the Semiconductor & Display Technology
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• v.19 no.2
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• pp.96-99
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• 2020

According to brilliant development of smart devices, many related services are being devised. And, almost every service is designed to provide user-centric services based on personal information. In this situation, to prevent unintentional leakage of personal information is essential. Conventionally, ID and Password system is used for the user authentication. This is a convenient method, but it has a vulnerability that can cause problems due to information leakage. To overcome these problem, many methods related to face recognition is being researched. Through this paper, we investigated the trend of user authentication through biometrics and a representative model for face recognition techniques. One is DeepFace of FaceBook and another is FaceNet of Google. Each model is based on the concept of Deep Learning and Distance Metric Learning, respectively. And also, they are based on Convolutional Neural Network (CNN) model. In the future, further research is needed on the equipment configuration requirements for practical applications and ways to provide actual personalized services.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.257-260
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• 2000

In modern battlefield situation, radar and infrared sensors may be located on aircraft having limited computational resources available for real-time computer processing. Hence sensor images are transmitted typically to central stations for processing and automatic target recognition/detection. Owing to the limited bandwidth channels that are typically available between the aircraft and processing stations, images are compressed prior to transmission to facilitate rapid transfer. In this paper we examine the problem of compressing sensor data for transmission, given that target recognition is the end goal. Performance result shows that the front-end target recognition system achieves a relatively high level of performance as well as a high compression ratio.

• Journal of the Korea Convergence Society
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• v.8 no.7
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• pp.323-330
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• 2017

Emotion in early childhood has been observed to make an important effect on behavioral development. The teacher has coached to develop good behavior based on considering emotional response rather than rational response. This study was to determine significance of emotional coaching for behavior development according emotion recognized by non-verbal measurement system developed specially in this study. The participants were 44 people and were asked to study in four experimental situation. The experiment was designed to four situation such as class without coaching, behavioral coaching, emotion coaching, and emotion coaching based on emotional recognition system. The dependent variables were subjective evaluation, behavioral amplitude, and HRC (Heart Rhythm Coherence) of heart response. The results showed the highest positive evaluation, behavioral amplitude, and HRC at emotion coaching based on emotional recognition system. In post-doc analysis, the subjective evaluation showed no difference between emotion coaching and system based emotion coaching. However, the behavioral amplitude and HRC showed a significant response between two coaching situation. In conclusion, quantitative data such as behavioral amplitude and HRC was expected to solve the ambiguity of subjective evaluation. The emotion coaching of teacher using emotional recognition system was can be to improve positive emotion and psychological stability for children.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.5
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• pp.53-59
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• 2018

Due to the recent developments in computer vision technology, complex actions can be recognized with reasonable accuracy in smart cities. In contrast, violence recognition such as events related to fight and knife, has gained less attention. The capability of visual surveillance can be used for detecting fight in streets or in prison centers. In this paper, we proposed a deep learning-based violence recognition method for surveillance cameras. A convolutional neural network (CNN) model is trained and fine-tuned on available benchmark datasets of fights and knives for violence recognition. When an abnormal event is detected, an alarm can be sent to the nearest police station to take immediate action. Moreover, when the probabilities of fight and knife classes are predicted very low, this situation is considered as normal situation. The experimental results of the proposed method outperformed other state-of-the-art CNN models with high margin by achieving maximum 99.21% accuracy.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.17-29
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• 2017

IRecently, researches on the recognition of indoor user situations through various sensors in a smart home environment are under way. In this paper, the case study was conducted to determine the operation of the robot vacuum cleaner by inferring the user 's indoor situation through the operation of home appliances, because the indoor situation greatly affects the operation of home appliances. In order to collect learning data for indoor situation awareness model learning, we received feedbacks from user when there was a mistake about the cleaning situation. In this paper, we propose a semi-supervised learning method using user feedback data. When we receive a user feedback, we search for the labels of unlabeled data that most fit the feedbacks collected through genetic algorithm, and use this data to learn the model. In order to verify the performance of the proposed algorithm, we performed a comparison experiments with other learning algorithms in the same environment and confirmed that the performance of the proposed algorithm is better than the other algorithms.

• IEMEK Journal of Embedded Systems and Applications
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• v.8 no.4
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• pp.185-194
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• 2013

Abstract- In distant-talking environments, speech recognition performance degrades significantly due to noise and reverberation. Recent work of Michael L. Selzer shows that in microphone array speech recognition, the word error rate can be significantly reduced by adapting the beamformer weights to generate a sequence of features which maximizes the likelihood of the correct hypothesis. In this approach, called Likelihood Maximizing Beamforming algorithm (Limabeam), one of the method to implement this Limabeam is an UnSupervised Limabeam(USL) that can improve recognition performance in any situation of environment. From our investigation for this USL, we could see that because the performance of optimization depends strongly on the transcription output of the first recognition step, the output become unstable and this may lead lower performance. In order to improve recognition performance of USL, some post-filter techniques can be employed to obtain more correct transcription output of the first step. In this work, as a post-filtering technique for first recognition step of USL, we propose to add a Wiener-Filter combined with Feature Weighted Malahanobis Distance to improve recognition performance. We also suggest an alternative way to implement Limabeam algorithm for Hidden Markov Network (HM-Net) speech recognizer for efficient implementation. Speech recognition experiments performed in real distant-talking environment confirm the efficacy of Limabeam algorithm in HM-Net speech recognition system and also confirm the improved performance by the proposed method.

• Journal of the Korea Safety Management & Science
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• v.10 no.2
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• pp.155-162
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• 2008

The ubiquitous, which is developed for human's convenience, uses the concept of situation awareness that communicates with computer and performs a certain work without user's recognition. In order to collect the information of situation, many devices are required. Also, in the condition of ubiquitous middleware, priority is given to effective controls of various devices. There are many devices for collecting the information of situation awareness such as sensor, RFID, etc. Among them, in the use of RFID, the researcher performed the experiment, in which multiple readers were used depending on the necessity of awareness information, and found the problem of intervention between readers occurring when multiple readers are used. The paper handles the problem of intervention causing from using multiple readers and suggests middleware design module using session manager to solve the problem.

• The Journal of the Korean dental association
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• v.53 no.8
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• pp.538-544
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• 2015

In a dental treatment, a dentist has to know the possibility to happen all kinds of the emergency and to prepare for managing that situation. Especially, the cardiac arrest is the most serious emergent problem. If the accident were happened, most dentists got embarrassed. The American Heart Association (AHA) is offering the Basic Life Support (BLS), Advanced Cardiopulmonary Life Support (ACLS) and Pediatric Advanced Life Support (PALS) programs for the healthcare who need to prepare the life threatening situation. The PALS is specialized to someone who participate in pediatric health-care field. This program is composed of three major emergency problems, such as respiratory emergencies, shock and cardiac arrests. The main concepts of the PALS are early recognition and systemic team approach. The purpose of this study was to introduce about PALS and to prepare response system for emergencies in the dental environment.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2011.06a
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• pp.144-146
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• 2011

VTS 항해의 특징은 동적복잡계의 특성을 보인다는 점이다. 자율적인 행위자들인 여러 선박이 서로 영향을 끼치며 상호작용하기 때문에 불확실성이 지배하게 된다. 이러한 불확실성으로 인한 위험을 극복하기 위한 방안으로 본 연구에서는 협력항해(co-navigation)이라는 개념을 중심으로 논의를 전개하였다. 본질적으로 협력항해는 수많은 상황판단과 의사결정들의 집합체이기 때문에 우선 개별 선박들의 상황판단이 어떻게 이루어지는가를 연구하는 것으로부터 출발하여야 한다. 따라서 본고에서는 항해에서 있어서의 상황자각이 어떻게 기능하는지 알아보고, 개인적인 상황판단에서 VTS 전체 차원의 최종 의사결정이 이루어지는 전 과정을 6단계로 세분하여 논의를 전개하였다. 이렇게 세분한 각 단계에서 양질의 인지과업이 이루어지도록 돕고, 이때 저지르게 되는 실수를 수정할 수 있도록 여유시간을 확보할 수 있도록 함으로써 궁극적으로 항해위험을 줄일 수 있다는 것을 이번 연구에서 밝히고자 하였다.