• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.171-179
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• 2013

Recognition and image processing technology depends on illumination variation. One of the most important factors is the parameters of algorithms. When it comes to select these values, the system has different types of recognition accuracy. In this paper, we propose performance improvement of the eye tracking system that depends on some environments such as, people, location, and illumination. Optimized threshold parameter was decided by using reinforcement learning. When the system accuracy goes down, reinforcement learning used to train the value of parameters. According to the experimental results, the performance of eye tracking system can be improved from 3% to 14% by using reinforcement learning. The improved eye tracking system can be effectively used for human-computer interaction.

• Science of Emotion and Sensibility
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• v.12 no.1
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• pp.129-136
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• 2009

Unlike former researches, this study for developing the caricature generator began observing the methods that other caricature experts have adopted. According to the observation, it seemed that experts tried to exaggerate characteristics of the target shape from other similar objects. When we are saying "This is similar to that," we give salience to their difference among the identical form groups. This study was to find the most similar geometry form to the target shape and then to transform its form through exaggeration. The research scope was restricted to exaggerate the outline shape of two-dimensional looped curve as a caricature form. For this, the author discussed the following: (a) organization method of four kinds of similar geometry form database, (b) search method to find the pertinent similar geometry form, (c) arrangement method for those searched data, and (d) method to exaggerate the target shape. Human faces and cars were selected as research categories to make the database. According to the survey over the transformed results, it was proved its possibility.

• Annual Conference of KIPS
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• 2022.11a
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• pp.565-567
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• 2022

질병을 앓고 있는 환자는 상태에 따라 병실, 주거지, 요양원 등 조호환경 내 생활 시 의료 인력의 지속적인 추적 및 관찰을 통해 신체에 이상이 생긴 경우 이를 감지하고, 신속하게 조치할 수 있도록 해야 한다. 의료 인력이 직접 환자를 확인하는 방법은 의료 인력의 반복적인 노동이 요구되며 실시간으로 환자를 확인해야 한다는 특성상 의료 인력이 상주해야 하기에 이는 곧, 의료 인력의 부족과 낭비로 이어진다. 해당 문제 해결을 위해 의료 인력을 대신하여 조호환경 내 환자의 상태를 실시간으로 모니터링할 수 있는 딥러닝 모델들이 연구되고 있다. 딥러닝 모델은 데이터의 수가 많을수록 강인한 모델을 설계할 수 있으며, 데이터셋의 배경, 객체의 특징 분포 등 다양한 조건에 영향을 받기 때문에 학습에 필요한 도메인을 가지는 많은 양의 전처리된 데이터를 수집해야 한다. 따라서, 조호환경 내 환자에 대한 데이터셋이 필요하지만, 공개된 데이터셋의 경우 양이 매우 적으며 이를 반전, 회전기법 등을이용할 경우 데이터의 수를 늘릴 수 있지만, 같은 분포의 특징을 가지는 데이터가 생성되기에 데이터 증강 기법을 단순하게 적용하면 딥러닝 모델의 과적합을 야기한다. 또한, 조호환경 내 이미지 데이터셋은 얼굴 노출과 같은 개인정보가 포함 될 수 있으며 이를 보호하기 위해 정보들을 비식별화 해야 한다는 문제점이 있다. 따라서 본 논문에서는 조호환경에서 수집된 데이터 증강을 위한 Style-Generative Adversarial Networks 기법을 적용하여 조호환경 데이터셋 수집에 효과적인 증강 기법을 제안한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1137-1144
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• 2022

In this study, an artificial intelligence(AI) was developed to help with facial expression practice in order to express emotions. The developed AI used multimodal inputs consisting of sentences and facial images for deep neural networks (DNNs). The DNNs calculated similarities between the emotions predicted by the sentences and the emotions predicted by facial images. The user practiced facial expressions based on the situation given by sentences, and the AI provided the user with numerical feedback based on the similarity between the emotion predicted by sentence and the emotion predicted by facial expression. ResNet34 structure was trained on FER2013 public data to predict emotions from facial images. To predict emotions in sentences, KoBERT model was trained in transfer learning manner using the conversational speech dataset for emotion classification opened to the public by AIHub. The DNN that predicts emotions from the facial images demonstrated 65% accuracy, which is comparable to human emotional classification ability. The DNN that predicts emotions from the sentences achieved 90% accuracy. The performance of the developed AI was evaluated through experiments with changing facial expressions in which an ordinary person was participated.

• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.18-23
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• 2016

Internet of things (IoT) is revolutionizing in the patient-Centered medical monitoring and management by authorizing the Smartphone application and data analysis with medical centers. The network connectivity is basic requirement to collect the observed human beings' health information from Smartphone to monitor the health from IoT medical devices in personal healthcare. The IoT environment built in Smartphone is very effective and does not demand infrastructure. This paper presents the smart phone deployed personal IoT architecture for Non-Invasive ECG Capturing. The adaptable IoT medical device cum Gateway is used for personal healthcare with big data storage on cloud configuration. In this approach, the Smartphone camera based imaging technique used to extract the personal ECG waveform and forward it to the cloud based big data storage connectivity using IoT architecture. Elaborated algorithm allows for efficient ECG registration directly from face image captured from Smartphone or Tablet camera. The profound technique may have an exceptional value in monitoring personal healthcare after adequate enhancements are introduced.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.397-414
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• 2016

There will be coming soon a sequence of the so-called election season in Korea. That is the 20th session of general elections and the 19th presidential election which are taking place one after another. When we talk about presidential candidate, we may realize that the choice were relied upon candidate's facial appearance and speech, voice, dress, and so on. One poll showed that capacity and policy were ranked high and figure and image were ranked next by asking "what is the most important factor when you vote for the president?" This study looked into the candidate's face of a newly elected public office through the election voting. I studied how the factors of sex and beauty may affect on the election results. I analyse survey of candidate's photo on the election leaflets. Analyzed result said that candidate's competency and trust have strong relations in the voting choice rather than beauty even if it is statistically significant. I also find that both beauty and competency are positively interrelated.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.157-167
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• 2022

This study attempted to investigate what kind of perception people in their 20s have about masks and to find out the characteristics of each type by categorizing the perception. The Q methodology was used for the study. The cognition types of masks were categorized into three. Type 1 was a 'always wear impact-important type' that always wears masks and thinks masks affect non-verbal communication and the wearer's image. Type 2 was a 'function-important negative recognition type' that wears masks to prevent germs and thinks that masks have a great negative impact. Type 3 was a 'concealment wear positive image type' that wears a mask to cover the face and thinks that a person looks young when wearing a mask. It is thought that the development of masks of various designs and functions reflecting the needs of consumers should be carried out. Also, it is thought that various products should be developed and sold so that consumers can choose according to important considerations such as design, fit, and function.

• Journal of Platform Technology
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• v.11 no.3
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• pp.56-67
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• 2023

Recently, de-identification of personal information, which has been a long-cherished desire of the data-based industry, was revised and specified in August 2020. It became the foundation for activating data called crude oil[2] in the fourth industrial era in the industrial field. However, some people are concerned about the infringement of the basic rights of the data subject[3]. Accordingly, a development study was conducted on the Batch De-Identification Tool, a personal information de-identification automation tool. In this study, first, we developed an image labeling tool to label human faces (eyes, nose, mouth) and car license plates of various resolutions to build data for training. Second, an object recognition model was trained to run the object recognition module to perform de-identification of personal information. The automated personal information de-identification tool developed as a result of this research shows the possibility of proactively eliminating privacy violations through online services. These results suggest possibilities for data-based industries to maximize the value of data while balancing privacy and utilization.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.427-434
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• 2022

The purpose of this study is to create a self-portrait that provides an immersive experience that immerses the viewer into the problem of self-awareness. We propose a method to implement an interactive self-portrait by using audio and image information obtained from viewers. The viewer's voice information is converted into text and visualized. In this case, the viewer's face image is used as pixel information composing the text. Text is the result of a mixture of one's own emotions, imaginations, and intentions based on personal experiences and memories. People have different interpretations of certain texts in different ways.The proposed digital self-portrait not only reproduces the viewer's self-consciousness in the inner aspect by utilizing the intertextuality of the text, but also expands the meanings inherent in the text. Intertextuality in a broad sense refers to the totality of all knowledge that occurs between text and text, and between subject and subject. Therefore, the self-portrait expressed in text expands and derives various relationships between the viewer and the text, the viewer and the viewer, and the text and the text. In addition, this study shows that the proposed self-portrait can confirm the formativeness of text and re-create spatial and temporality in the external aspect. This dynamic self-portrait reflects the interests of viewers in real time, and has the characteristic of being updated and created.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.41-43
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• 2022

In order to prevent and block infectious diseases caused by the recent COVID-19 pandemic, non-contact biometric information acquisition and analysis technology is attracting attention. The invasive and attached biometric information acquisition method accurately has the advantage of measuring biometric information, but has a risk of increasing contagious diseases due to the close contact. To solve these problems, the non-contact method of extracting biometric information such as human fingerprints, faces, iris, veins, voice, and signatures with automated devices is increasing in various industries as data processing speed increases and recognition accuracy increases. However, although the accuracy of the non-contact biometric data acquisition technology is improved, the non-contact method is greatly influenced by the surrounding environment of the object to be measured, which is resulting in distortion of measurement information and poor accuracy. In this paper, we propose a context-based bio-signal modeling technique for the interpretation of personalized information (image, signal, etc.) for bio-information analysis. Context-based biometric information modeling techniques present a model that considers contextual and user information in biometric information measurement in order to improve performance. The proposed model analyzes signal information based on the feature probability distribution through context-based signal analysis that can maximize the predicted value probability.