• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.877-885
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• 2022

Vision-based activity recognition has been widely attempted at construction sites to estimate productivity and enhance workers' health and safety. Previous studies have focused on extracting an individual worker's postural information from sequential image frames for activity recognition. However, various trades of workers perform different tasks with similar postural patterns, which degrades the performance of activity recognition based on postural information. To this end, this research exploited a concept of human-object interaction, the interaction between a worker and their surrounding objects, considering the fact that trade workers interact with a specific object (e.g., working tools or construction materials) relevant to their trades. This research developed an approach to understand the context from sequential image frames based on four features: posture, object, spatial features, and temporal feature. Both posture and object features were used to analyze the interaction between the worker and the target object, and the other two features were used to detect movements from the entire region of image frames in both temporal and spatial domains. The developed approach used convolutional neural networks (CNN) for feature extractors and activity classifiers and long short-term memory (LSTM) was also used as an activity classifier. The developed approach provided an average accuracy of 85.96% for classifying 12 target construction tasks performed by two trades of workers, which was higher than two benchmark models. This experimental result indicated that integrating a concept of the human-object interaction offers great benefits in activity recognition when various trade workers coexist in a scene.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권2호
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• pp.800-816
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• 2018

In recent years, video surveillance research has been able to recognize various behaviors of pedestrians and analyze the overall situation of objects by combining image analysis technology and deep learning method. Human Activity Recognition (HAR), which is important issue in video surveillance research, is a field to detect abnormal behavior of pedestrians in CCTV environment. In order to recognize human behavior, it is necessary to detect the human in the image and to estimate the pose from the detected human. In this paper, we propose a novel approach for 2D Human Pose Estimation based on object detection using RGB-D information. By adding depth information to the RGB information that has some limitation in detecting object due to lack of topological information, we can improve the detecting accuracy. Subsequently, the rescaled region of the detected object is applied to ConVol.utional Pose Machines (CPM) which is a sequential prediction structure based on ConVol.utional Neural Network. We utilize CPM to generate belief maps to predict the positions of keypoint representing human body parts and to estimate human pose by detecting 14 key body points. From the experimental results, we can prove that the proposed method detects target objects robustly in occlusion. It is also possible to perform 2D human pose estimation by providing an accurately detected region as an input of the CPM. As for the future work, we will estimate the 3D human pose by mapping the 2D coordinate information on the body part onto the 3D space. Consequently, we can provide useful human behavior information in the research of HAR.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권6호
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• pp.3104-3120
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• 2017

The intelligent monitoring system has been successfully applied in many fields such as: monitoring of production lines, transportation, etc. Smart surveillance systems have been developed and proven effective in some specific areas such as monitoring of human activity, traffic, etc. Most of critical application monitoring systems involve object tracking as one of the key steps. However, task of tracking of moving object is not easy. In this paper, the authors propose a method to implement human object tracking in outdoor environment based on human features in shearlet domain. The proposed method uses shearlet transform which combines the human features with context-sensitiveness in order to improve the accuracy of human tracking. The proposed algorithm not only improves the edge accuracy, but also reduces wrong positions of the object between the frames. The authors validated the proposed method by calculating Euclidean distance and Mahalanobis distance values between centre of actual object and centre of tracked object, and it has been found that the proposed method gives better result than the other recent available methods.

• 한국멀티미디어학회논문지
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• 제24권3호
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• pp.416-422
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• 2021

Due to the large differences in human activity within classes, the large similarity between classes, and the problems of visual angle and occlusion, it is difficult to extract features manually, and the detection rate of human behavior is low. In order to better solve these problems, an improved Faster R-CNN-based detection algorithm is proposed in this paper. It achieves multi-object recognition and localization through a second-order detection network, and replaces the original feature extraction module with Dense-Net, which can fuse multi-level feature information, increase network depth and avoid disappearance of network gradients. Meanwhile, the proposal merging strategy is improved with Soft-NMS, where an attenuation function is designed to replace the conventional NMS algorithm, thereby avoiding missed detection of adjacent or overlapping objects, and enhancing the network detection accuracy under multiple objects. During the experiment, the improved Faster R-CNN method in this article has 84.7% target detection result, which is improved compared to other methods, which proves that the target recognition method has significant advantages and potential.

• 인터넷정보학회논문지
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• 제18권6호
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• pp.85-92
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• 2017

최근 영상감시 분야에서는 영상에서 움직이는 사람을 탐지하고, 탐지된 사람의 행위를 분석하는 방식에 딥러닝 기반 학습방법이 적용되기 시작했다. 이러한 지능형 영상분석 기술을 적용할 수 있는 분야 중 하나인 인간 행위 인식은 객체를 탐지하고 탐지된 객체의 행위를 인식하기 위해 신체 키포인트를 검출 하는 과정을 거치게 된다. 본 논문에서는 RGB-D 정보를 이용한 객체 탐지 기반의 신체 키포인트 검출 방법을 제시한다. 먼저, 두 대의 카메라로 생성된 색상정보와 깊이정보를 이용하여 이동하는 객체를 배경으로부터 분할하여 탐지한다. RGB-D 정보를 이용하여 탐지된 객체의 영역을 재조정하여 생성된 입력 데이터를 한 사람의 자세 추정을 위한 Convolutional Pose Machines(CPM)에 적용한다. CPM을 이용하여 한 사람당 14개의 신체부위에 대한 신념 지도(Belief Map)를 생성하고, 신념 지도를 기반으로 신체 키포인트를 검출한다. 이와 같은 방법은 키포인트를 검출할 객체에 대한 정확한 영역을 제공하게 되며, 개별적인 신체 키포인트의 검출을 통하여 단일 신체 키포인트 검출에서 다중 신체 키포인트 검출로 확장 할 수 있다. 향후, 검출된 키포인트를 이용하여 인간 자세 추정을 위한 모델을 생성할 수 있으며 인간 행위 인식 분야에 기여 할 수 있다.

• 한국정보통신학회논문지
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• 제16권6호
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• pp.1179-1186
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• 2012

본 논문에서는 인체의 조인트와 조인트의 움직임 정보를 이용하여 인간의 행동을 인식하는 알고리즘을 제안한다. 제안방법은 입력되는 비디오에서 객체를 추출하고 인체의 비율정보를 이용하여 조인트를 자동추출하며 각 조인트에 블록매칭 기법을 적용하여 조인트의 움직임 정보를 얻는다. 제안방법은 움직임이 있는 조인트, 조인트의 움직임의 방향벡터와 조인트의 x와 y좌표의 증가(+)와 감소(-)를 부호로 나타낸 것을 행동 인식을 위한 기본 파라메터로 사용한다. 제안된 방법은 웹카메라에서 입력되는 영상에서 8가지 행동에 대해 실험하였으며 인간의 행동 인식률에 있어 좋은 결과를 보였다.

• 디자인학연구
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• 제9권
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• pp.801-810
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• 1994

Design Problems are often both multidimensional and highly interactive. Very rarely does any part of a designed thing serve only one purpose. The activity of designing is thus a goal-directed activity and normally a goal-directed problem-solving activity. This means, problem solving is finding a way to get from some initial situation to a desired goal. Designers are transforming agents within a society whose goals are to improve the human condition through physical metamorphosis. Many theorist have agreed that designing involves problem solving or decision making. Accordingly evaluation plays an essential role in design activity. The evaluation factors include all attributes that have levels specified by quantitative and qualitative objectives Alternatives in multi-objective decision prOblems generally possess numerous attributes by which they can be described and compared. The evaluation factors include all attributes that have levels specified by quantitative and qualitative objectives. However since qualitative factors are difficult to quantify as numeral estimates, these factors have tended to be ignored without regard for their importance to human content. We adapted the Accumulative Evaluation Model as an evaluation algorithm for IDES. Industrial Design Evaluation System (IDES) consists of 3 major modules ( 1 Design Element, 2.Matrix, 3.Evaluation). It is intended to be an aid for design evaluation. The luther thinks IDES is a new design evaluation approach which could provide effective rating of design values to make value judgements. It is an attempt to provide industrial designers with access to design evaluation. The author's aim is to produce an Object-Oriented Evaluation System which can guide the designers and decision makers under complex design projects. It uses\ulcorner an Object-Oriented Programming for this prototype, Because of managing complexity (Flexibility and Reusability) and improving productivity(Extensibility & Maintainability and Programming by User) in software development process. The author has chose the C++ because it is a hybrid, rather than pure Object-Oriented Language.

• 한국정보시스템학회:학술대회논문집
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• 한국정보시스템학회 2000년도 추계학술대회
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• pp.12-15
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• 2000

An SADT-based methodology is presented for systematically analyzing the container working process in container terminal, as well as an object-oriented design method for an integrated information system for container terminal resource planning and management. Our design architecture is composed of four levels, activity interface, activity PDCA control, human resource management, and facility resource management. Especially, the consideration of the human resource management level makes it possible to support cooperative tasks, to make the authority and responsibility on a task clear, and to extremely promote the balance between human and facility resources. Finally, The system architecture is suggested for Virtual Container Terminal, in which a planned container working process is simulated for previous feasibility check, work orders are transferred to control real devices, and to manage the entire process and related data.

• Transactions on Control, Automation and Systems Engineering
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• 제4권1호
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• pp.43-48
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• 2002

We show that humans execute the postural control ingeniously by regulating the impedance properties of the musculo-skeletal system as the motor command against the alteration of the environment. Adjusting muscle activity can control the impedance properties of the musculo-skeletal system. To quantify the changes in human arm viscoelasticity on the vertical plane during interaction with the environment, we asked our subject to hold an object. By utilizing surface electromyographic(EMG) studies, we determined a relationship between the perturbation and a time-varying muscle co-activation. Our study showed when the subject lifts the object by himself the muscle stiffness increases while the torque remains the same just before the lift-off. These results suggest that the central nervous system(CNS) simultaneously controls not only the equilibrium point(EP) and the torque, but also the muscle stiffness as themotor command in posture control during the contact task.

• 복식
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• 제6권
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• pp.145-160
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• 1982

Wearing a clothes in human living is very rightful and reasonable things. And it's also the necessaries of living. So now, I want look around about origin of clothes from the prehistorical age, how they start and why they need to wear a clothes. As human culture is unknown origin, human clothes origin is also unknown origin, too. So many different people made unlike story about that, and it is very difficult to say correct birth of clothes. It must be reflection by a time, by a place, by a mankind, until this days, the history of human progress is $2,000,000{\sim}3,000,000$ years. And from after the "Old Adam" man understand what is shame and disgrace, so that made them cover of their private parts, also it is a motive of human clothes. Since after pass a long time, the earth has many changes as it were weather, and for take care of human body from cold, people start make clothes and it's a second object of wearing a clothes. And third object of wearing clothes is after opportunity of development human culture, people desire for an aesthetic sence and for full-fill that feeling they start make a beautiful clothes with accessories and it is motive and a purpose of a human start wear a clothes. So I can say, for origin birth of clothes is 1. Protect of human body. 1) be adapted for different weather and different circumstance. 2) take care self from outside injurg. 2. Decorate for aesthetic sence. 1) Theory of Amulets. 2) Theory of symbolism. 3) Theory of Sex attraction. 4) Aesthetic Theory. 5) Theory of chastity. 6) Multi-theory And material for clothes they made from natural wilds like leaves, fur, skin of wood. skin of fishes and feather etc. But after develop of human knowledge people invent fiber, and use a knitted goods and woven stuff also first of all. They start use those kind that they just cover of their private parts as a belt and astring with leaves and a beast skins. But until this days it's taken big development with human knowledge and most important influence of develop was weather. So modern clothes for present days, must care with. physicology, preservation of health, living activity, dressing, morals, and etiquette etc.