• Electronics and Telecommunications Trends
• /
• v.27 no.4
• /
• pp.114-122
• /
• 2012

최근 CCTV(Closed Circuit Television)의 설치가 증가하면서 효율적인 모니터링을 위하여 지능형 영상분석 기술에 대한 관심이 높아지고 있다. 지능형 영상분석 기술은 영상의 정보를 분석하여 자동으로 이상 행위를 탐지하고 관리자에게 경보를 전송하는 기술로써, 사고를 사전에 예방하고 사고가 발생한 경우에는 신속하게 대응하여 피해를 줄일 수 있게 해준다. 본고에서는 지능형 영상분석 기술이 탐지할 수 있는 이상 행위, 즉 이벤트를 그 목적에 따라서 보안, 비즈니스 인텔리전스, 객체인식으로 구분하여 현재 기술 수준을 살펴볼 것이다. 그리고 앞으로 지능형 영상분석에서 이벤트 탐지 기술의 발전 방향을 사람의 행동인식, 행위 기반 이상 현상 탐지, 군중 환경에서 이벤트 탐지, 지능형 영상분석 구조의 변화 등의 관점으로 구분하여 살펴보고자 한다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2015.10a
• /
• pp.1396-1398
• /
• 2015

BCI (Brain Computer Interface)는 사람의 두뇌와 컴퓨터를 연결하는 '뇌-컴퓨터 인터페이스'를 나타내는 것이며 EEG(Electroencephalogram)을 주로 분석하여 인간의 행동이나 의도를 파악한다. 본 논문에서는 EEG를 이용한 행동인식의 하나로 졸음을 판단하는 방법을 제안한다. 제안방법에서는 MindWave를 이용하여 얻은 실험 데이터를 FFT를 이용하여 1초 단위로 스펙트럼을 분석하여 High-Alpha 영역의 시간에 따른 데이터 변화 패턴을 분석하여 졸음을 판단한다. 실험 결과, 100%의 최고 성능을 얻을 수 있었다.

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

• Journal of the Korean Institute of Intelligent Systems
• /
• v.24 no.6
• /
• pp.597-602
• /
• 2014

We propose hybrid-sensing system for human tracking. This system uses laser scanners and image sensors and is applicable to wide and crowded area such as hallway of university. Concretely, human tracking using laser scanners is at base and image sensors are used for human identification when laser scanners lose persons by occlusion, entering room or going up stairs. We developed the method of human identification for this system. Our method is following: 1. Best-shot images (human images which show human feature clearly) are obtained by the help of human position and direction data obtained by laser scanners. 2. Human identification is conducted by calculating the correlation between the color histograms of best-shot images. It becomes possible to conduct human identification even in crowded scenes by estimating best-shot images. In the experiment in the station, some effectiveness of this method became clear.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.12
• /
• pp.536-546
• /
• 2020

This study examined the correlation between safety practices and safety knowledge, safety awareness and safety efficacy, and the factors influencing the safety practices of in-home child-care providers. The participants were 199 in-home child-care providers who worked at two cities in G province. Using a structured-questionnaire, the data were collected from December 2019 to January 2020. The data were analyzed using the IMB/SPSS 25.0 program. The collected data were analyzed using descriptive statistics (frequency, percent, mean, and SD), a t-test, ANOVA, Scheff test, Pearson Correlation Coefficient, and multiple regression. The mean score for safety knowledge, safety awareness, safety efficacy, and safety practices were 0.64 (SD, 0.09), 1.92 (SD, 0.37), 4.18 (SD, 0.51), and 2.55 (SD, 0.36), respectively. Safety practices were positively correlated with the safety knowledge (r=.14, p=.042), safety efficacy (r=.43, p<.001), and sub-factors of safety efficacy, self-regulation (r=.32, p<.001), enlisting social support (r=.40, p<.001), and controlling the environment (r=.39, p<.001). Enlisting social support and controlling the environment, sub-factors of safety efficacy were influenced safety practices significantly and explained 20.0% of the variance. Based on these findings, it will be necessary to develop a program that can enhance their safety efficacy for safety practices of in-home child-care providers.

• Journal of Internet Computing and Services
• /
• v.20 no.3
• /
• pp.101-109
• /
• 2019

Based on the electricity sales and public consumption psychology during the online shopping festival, the purpose of this study is to investigate the factors that influence the reusing intention of the online shopping festival consumers. This research is focusing on The Theory of Reasoned Action(TRA) and The Technology Acceptance Model(TAM) to understand online shopping festival consumers' decision making process. The sampling is Chinese from 20s to 50s, who had participated in the online shopping festival.Findings suggests that first, the positive attitude of online shopping festival and subjective norms showed positive effects on online shopping festival consumers' reusing intention. Second, perceived usefulness, perceived ease and perceived enjoyment had statistically significant effects on online shopping festival consumers' reusing intention. Third, according to perceived risk perception of online shopping festivals, there were differences in factors affected the online shopping festival's reusing intention. In particular, the perceived ease of people who perceived risk higher, and the perceived usefulness of people who perceived risk lower had greatest impacts on reusing intention. Based on these findings, the implications and limitations of this study were discussed and suggestions for subsequent studies.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.9 no.10
• /
• pp.1095-1102
• /
• 2014

In this paper, We proposed the approach of GPU and motion vector to analysis the Human activity in real-time surveillance system. The most important part, that is detect blob(human) in the foreground. We use to detect Adaptive Gaussian Mixture, Weighted subtraction image for salient motion and motion vector. And then, We use motion vector for human activity analysis. In this paper, the activities of human recognize and classified such as meta-classes like this {Active, Inactive}, {Position Moving, Fixed Moving}, {Walking, Running}. We created approximately 300 conditions for the simulation. As a result, We showed a high success rate about 86~98%. The results also showed that the high resolution experiment by the proposed GPU-based method was over 10 times faster than the cpu-based method.

• 한국HCI학회:학술대회논문집
• /
• 2008.02a
• /
• pp.348-353
• /
• 2008

This paper proposes a novel touch interface for recognizing user's touch pattern and understanding emotional information by eliciting natural user interaction. To classify physical touches, we represent the similarity between touches by analyzing touches based on its dictionary meaning and design the algorithm to recognize various touch patterns in real time. Finally we suggest the methodology to estimate user's emotional state based on touch.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2020.07a
• /
• pp.601-602
• /
• 2020

본 연구에서는 질적연구방법인 Q방법론을 적용하여 대학생들을 대상으로 학과 점퍼에 대해서 어떤 생각을 가지고 있는지에 대한 주관적 평가와 인식 유형별 특성을 알아보고자 하였다. 제1유형의 경우 학과 점퍼는 학과에 대한 소속감을 주고 학과를 홍보하는 역할을 한다고 인식하였다. 또, 학과 점퍼를 착용하면 행동을 조심하게 되지만, 활동이 편하고 주변 사람들의 좋은 평가를 이끌어내며 나의 신뢰감을 높여주는 효과가 있다고 생각하는 것으로 분석되었다. 제2유형의 경우 학과 점퍼는 활동하기 편하고 유행을 따르지 않는 무난한 디자인이라 만족스러우며, 학교 갈 때 늘 착용한다고 하였다. 제3유형은 학과 점퍼를 착용하면 동질감과 소속감을 준다고 하였고, 학과 점퍼가 유행을 따라가는 스타일이면 좋겠다고 생각하며 학과 점퍼 착용에 긍정적이고 잘 맞는다고 생각하는 유형이다. 대학생들의 학과 점퍼도 하나의 유니폼으로써 기능을 할 수 있도록 학과의 이미지나 상징성을 잘 나타내고, 활동량이 많은 대학생들의 신체적 특징을 반영하여 맞음새가 우수한 학과 점퍼가 개발되어야 할 것으로 생각된다.

• Electronics and Telecommunications Trends
• /
• v.32 no.1
• /
• pp.54-60
• /
• 2017

사물인터넷은 모든 사람과 사물이 인터넷을 통해 서로 소통하고 새로운 가치를 창출할 수 있는 기술이며, 정보의 확산, 연계, 활용을 가능하게 하는 중요한 연결고리이다. 인지 IoT는 이러한 사물인터넷 인프라와 함께 인공지능 기술을 활용하여, 사물이 스스로 생각하고 판단하며, 보다 잘 연결하고 더 똑똑해지도록 하는 사물지능 실현 기술이다. 본고는 인간 두뇌의 기능을 모방하여 인식, 행동, 인지 능력을 재현해내는 대표 인지 컴퓨팅 기술인 IBM 왓슨, 딥 러닝, 뉴로모픽칩 기술을 요약하며, 또한, 사물수준 지능 실현 사례인 IBM 쿼크, CISCO DMo와 D3의 개발 현황을 소개한다.