• 전기학회논문지
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• 제59권12호
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• pp.2314-2318
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• 2010

For human-robot interaction, a robot should recognize the meaning of human behavior. In the case of static behavior such as face expression and sign language, the information contained in a single image is sufficient to deliver the meaning to the robot. In the case of dynamic behavior such as gestures, however, the information of sequential images is required. This paper proposes behavior classification by using fuzzy classifier to deliver the meaning of dynamic behavior to the robot. The proposed method extracts feature points from input images by a skeleton model, generates a vector space from a differential image of the extracted feature points, and uses this information as the learning data for fuzzy classifier. Finally, we show the effectiveness and the feasibility of the proposed method through experiments.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2023년도 추계학술발표대회
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• pp.634-636
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• 2023

Surveillance systems play a pivotal role in ensuring the safety and security of various environments, including public spaces, critical infrastructure, and private properties. However, detecting abnormal human behavior in lowlight conditions is a critical yet challenging task due to the inherent limitations of visual data acquisition in such scenarios. This paper introduces a spatiotemporal framework designed to address the unique challenges posed by low-light environments, enhancing the accuracy and efficiency of human abnormality detection in surveillance camera systems. We proposed the pre-processing using lightweight exposure correction, patched frames pose estimation, and optical flow to extract the human behavior flow through t-seconds of frames. After that, we train the estimated-action-flow into autoencoder for abnormal behavior classification to get normal loss as metrics decision for normal/abnormal behavior.

• 한국디자인학회:학술대회논문집
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• 한국디자인학회 1995년도 디자인 학 연구 1995년 추계 학술연구 발표 대회 개요 집
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• pp.36-37
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• 1995

• 한국콘텐츠학회논문지
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• 제17권9호
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• pp.650-660
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• 2017

본 연구는 지금까지의 서사 양식에 등장했던 캐릭터의 성격 유형론을 정리하여, 기존의 캐릭터의 성격 유형론이 갖고 있는 문제점을 정리하고 새로운 분류 가능성을 제안하기 위한 것이다. 지금까지 서사 이론에서 캐릭터 유형의 분류는 크게 서사 내에서의 역할이라는 형식적인 분류와 인간의 내적 자질에 근거한 내용적인 분류, 그리고 그 두 가지 분류 기준이 착종된 보완적 분류로 이루어져 있었다. 기존 캐릭터 분류 유형이 담고 있는 문제는 바로 인간의 내적 자질에 근거한 내용적인 분류의 유용성에 비해 실질적으로 분류가 어렵다는 점이다. 반면 서사 내 등장인물의 역할에 따른 분류는 그 분류가 형식적이기 때문에 서사론의 발전상 중요하게 다뤄져 왔지만, 그다지 실질적인 분석 방법론으로 기능하기는 어려웠다. 본 연구는 이러한 문제를 해결하기 위한 시론적인 성격으로, 샬롬 슈워츠의 인간의 가치 유형을 도입하여, 인간의 가치 유형과 인간의 역할을 상호 관련시켜 새로운 캐릭터 분석 방법의 가능성을 제안하고자 한다. 슈워츠의 가치 유형 연구는 인간의 행동의 동기를 파악하는 데 매우 효과적인 방법론으로, 등장인물의 지향성을 분석하는 데 큰 의미가 있을 것이다.

• 한국안전학회지
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• 제39권1호
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• pp.82-95
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• 2024

Analyzing the aftermath of events at domestic nuclear power plants brings in the question: "Why do workers not comply with the prescribed procedures?" The current investigation of nuclear power plant events identifies their reasons considering the factors affecting the workers' behaviors. However, there are some complications to it: in addition to confirming the action such as an error or a violation, there is a limit to identifying the intention of the actor. To overcome this limitation, the study analyzed and examined the reasons for non-compliance identified in nuclear power plant events by Reason's rule-related behavior classification. For behavior analysis, I selected unit behaviors for events that are related to human and organizational factors and occurred at domestic nuclear power plants since 2017, and then I applied the rule-related behavior classification introduced by Reason (2008). This allowed me to identify the intentions by classifying unit behaviors according to quality and compliance with the rules. I also identified the factors that influenced unit behaviors. The analysis showed that most often, non-compliance only pursued personal goals and was based on inadequate risk appraisal. On the other hand, the analysis identified cases where it was caused by such factors as poorly written procedures or human system interfaces. Therefore, the probability of non-compliance can be reduced if these factors are properly addressed. Unlike event investigation techniques that struggle to identify the reasons for employee behavior, this study provides a new interpretation of non-compliance in nuclear power plant events by examining workers' intentions based on the concept of rule-related behavior classification.

• 한국멀티미디어학회논문지
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• 제23권12호
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• pp.1540-1551
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• 2020

Aiming at the problem that the existing human behavior recognition algorithm cannot fully utilize the multi-level spatio-temporal information of the network, a human behavior recognition algorithm based on a dense three-dimensional residual network is proposed. First, the proposed algorithm uses a dense block of three-dimensional residuals as the basic module of the network. The module extracts the hierarchical features of human behavior through densely connected convolutional layers; Secondly, the local feature aggregation adaptive method is used to learn the local dense features of human behavior; Then, the residual connection module is applied to promote the flow of feature information and reduced the difficulty of training; Finally, the multi-layer local feature extraction of the network is realized by cascading multiple three-dimensional residual dense blocks, and use the global feature aggregation adaptive method to learn the features of all network layers to realize human behavior recognition. A large number of experimental results on benchmark datasets KTH show that the recognition rate (top-l accuracy) of the proposed algorithm reaches 93.52%. Compared with the three-dimensional convolutional neural network (C3D) algorithm, it has improved by 3.93 percentage points. The proposed algorithm framework has good robustness and transfer learning ability, and can effectively handle a variety of video behavior recognition tasks.

• 대한인간공학회지
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• 제31권4호
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• pp.533-540
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• 2012

Objective: This paper targets a framework of a hand gesture based interface design. Background: While a modeling of contact-based interfaces has focused on users' ergonomic interface designs and real-time technologies, an implementation of a contactless interface needs error-free classifications as an essential prior condition. These trends made many research studies concentrate on the designs of feature vectors, learning models and their tests. Even though there have been remarkable advances in this field, the ignorance of ergonomics and users' cognitions result in several problems including a user's uneasy behaviors. Method: In order to incorporate compatibilities considering users' comfortable behaviors and device's classification abilities simultaneously, classification-oriented gestures are extracted using the suggested human-hand model and closed-loop classification procedures. Out of the extracted gestures, the compatibility-oriented gestures are acquired though human's ergonomic and cognitive experiments. Then, the obtained hand gestures are converted into a series of hand behaviors - Handycon - which is mapped into several functions in a mobile device. Results: This Handycon model guarantees users' easy behavior and helps fast understandings as well as the high classification rate. Conclusion and Application: The suggested framework contributes to develop a hand gesture-based contactless interface model considering compatibilities between human and device. The suggested procedures can be applied effectively into other contactless interface designs.

• 한국안전학회지
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• 제33권1호
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• pp.66-72
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• 2018

This study analyses the types, related operations, facilities, and causes of chemical accidents in Korea based on the RISCAD classification taxonomy. In addition, human error analysis was carried out employing different human error classification criteria. Explosion and fire were major accident types, and nearly half of the accidents occurred during maintenance operation. In terms of related facility, storage devices and separators were the two most frequently involved ones. Results of the human error-based analysis showed that latent human errors in management level are involved in many accidents as well as active errors in the field level. Action errors related to unsafe behavior leads to accidents more often compared with the checking behavior. In particular, actions missed and inappropriate actions were major problems among the unsafe behaviors, which implicates that the compliance with the work procedure should be emphasized through education/training for the workers and the establishment of safety culture. According to the analysis of the causes of the human error, the frequency of skill-based mistakes leading to accidents were significantly lower than that of rule-based and knowledge based mistakes. However, there was limitation in the analysis of the root causes due to limited information in the accident investigation report. To solve this, it is suggested to adopt advanced accident investigation system including the establishment of independent organization and improvement in regulation.

• 한국디자인학회:학술대회논문집
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• 한국디자인학회 2004년도 추계 학술발표대회 논문집
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• pp.154-155
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• 2004

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2019년도 춘계학술대회
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• pp.395-397
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• 2019

조선기술과 항해장비 기술이 발전하고 있지만 여전히 해양사고는 80%이상이 인적과실에서 비롯되고 있다. 인적과실을 저감시켜 해양사고를 절감시키려는 노력은 항해사를 대상으로 면담이나 설문을 시행하는 등 정성적인 연구방식에 많이 의존하고 있어서 객관적인 인적과실의 실체를 규명하는데 제한이 있다. 본 연구에서는 이 같은 단점을 극복하기 위하여 항해사의 항해 업무 수행을 방해하지 않으며 공간적 제한을 극복할 수 있도록 웨어러블 센서를 활용하여 항해사의 동작을 실측하고 상황인지 여부가 항해 수행 동작에 어떤 영향을 미치는지 구분하고자 한다. Full mission ship handling simulator를 활용하여 항해사가 특정한 시나리오를 수행하는 중에 위험성을 가진 장애물을 발견하기 전과 후의 어떤 행동패턴 변화를 보이는지 측정하였다. 구분된 항해 동작 패턴은 항해 위험 상황에서 적절한 조치를 취하고 있는지 여부를 객관적으로 구분하여 인적과실을 절감하는데 활용될 것으로 기대된다.