• 한국멀티미디어학회논문지
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• 제20권8호
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• pp.1248-1257
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• 2017

We propose a frequency estimation algorithm of human movements using Kinect. We collect the 3D coordinates of the joints of a human body and then obtain the frequency-domain description of the movements using the discrete Fourier transform (DFT). By choosing the frequency with the biggest magnitude in the selected frequencies of each of human's joint, we obtain the major beat of the human movements. Experimental results show that the proposed algorithm accurately estimates the frequency of human movements. We expect that the proposed algorithm would be applied to many AR and VR applications as a preprocessing.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 D
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• pp.2356-2358
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• 2004

This thesis aims to investigate new approaches to the control strategies of human arm movements and its application for the human interface. By analyzing myoelectric signal(MES) from the arm movements of the normal human subjects, neurological informations obtained patterned could be used to identify different movement patterns of the arm movement. In this paper Artificial neural network for separation of the contraction patterns of four kinds of arm movements, i.e. and flexion and extension of the elbow and adduction and abduction of the forearm were adopted through computer simulation and experiments results were compared with the experimental added-load arm movements.

• 한국안전학회지
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• 제20권4호
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• pp.114-121
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• 2005

Railroad shunting movements connecting and disconnecting train sets are very susceptible to human errors since they depend on human decision-making and action procedure that are variable to situation to situation. Nevertheless, in the investigation of railroad accidents, all the accident causes related with human factors have merely been categorized as 'careless treatment' of the workers without any systematic approach of behavioral sciences or the analysis of human errors. In this research, therefore, 137 accident cases occurred during railroad shunting movements and 435 accident cases occurred during driving were analyzed with a special interest of human errors. According to results, the traditional accident investigation scheme used for last several decades did not seem to be appropriate for catching up true accident causes with respect to human errors. In addition, both signal men and locomotive drivers made many mistakes in judgement/action stage while the former mainly commit judgement tasks where as the latter mainly commit cognition tasks. Ant those tasks such as 'confirmation of signal and route', 'location check-up of connected train sets', and 'route identification for a shift of track' ranked highly for accident susceptibility.

• 한국멀티미디어학회논문지
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• 제8권6호
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• pp.844-855
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• 2005

This paper proposes a human action recognition scheme for Intelligent Web Browser. Based on the principle that a human action can be defined as a combination of multiple articulation movements, the inference of stochastic grammars is applied to recognize each action. Human actions in 3 dimensional (3D) world coordinate are measured, quantized and made into two sets of 4-chain-code for xy and zy projection planes, consequently they are appropriate for applying the stochastic grammar inference method. We confirm this method by experiments, that various physical actions can be classified correctly against a set of real world 3D temporal data. The result revealed a comparatively successful achievement of $93.8\%$ recognition rate through the experiments of 8 movements of human head and $84.9\%$ recognition rate of 60 movements of human upper body. We expect that this scheme can be used for human-machine interaction commands in a web browser.

• 한국실내디자인학회논문집
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• 제21권1호
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• pp.103-110
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• 2012

With a theoretical focus on the emotional experiences created via the interface, and the relationship between human beings and space, this study aims to corroborate and clarify the formation and verification of emotional interactions between human beings and space using body movements. It follows the method of Coining "Movement Phrases" through the analysis of body movements in the experimental space, thereby developing them into a complete scenario to produce the story of emotional expression. This study has hereby generated the following outcomes: First, the "pocket-type" exhibition displays a higher frequency of body movements than the "general" exhibition. It has close connections with emotional vocabularies: "Curious," "interesting," "warm," and "fun." The "general" exhibition records a relatively high frequency of emotional vocabularies like "natural," "efficient," and "free." Second, it is possible to analyze the story of space using a scenario, just like drama, based upon attributes and serial relationships. The "exposition" section reveals a high degree of "curiosity" and a large number of body movements, while the "development" section indicates high degree of "surprise" plus slight body movements. The "transition" sections manifest high "interest" and many body movements, and the "climax" section shows a high frequency of "surprise" and many changes in body movements. The "conclusion" section finally invokes images together with body movements.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -3
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• pp.1886-1888
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• 2002

Non-verbal information plays an important role not only in human-to-human communications but also in human computer interaction. In this paper, we examine effects of human-like agent's primitive movements on user's impression, where the human-like agent's primitive movements include eye, mouth, and head. SD (Semantic Differential) method was used for evaluation, and two factors were extracted as a result of the factor analysis. It is found that the first factor influenced the user's impression particularly.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 하계학술대회 논문집
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• pp.799-804
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• 1991

This paper is concerned with the artificial control of prosthetic devices using the electromyographic(EMG) activities of biceps and triceps in human subject during isometric contraction adjustments at the elbow. And it was analysised about recognition of EMG signals and dynamic characteristics at arm movements of human. For this study the error signal of autoregressive(AR) model were used to discriminate arm movement patterns of human. Interaction of dynamic characteristics (Position, Velocity, Acceleration) and EMG of biceps and triceps at arm movements of human was measured.

• 한국실내디자인학회:학술대회논문집
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• 한국실내디자인학회 2004년도 춘계학술발표대회 논문집
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• pp.176-179
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• 2004

Space is comprised by the movements of human beings, and draws a complex locus within it. That form seems to be complex of movement around in all directions of space axis, and be ever-changing process as time goes by. Although Human are able to move uninhibitedly, the movements are restricted to a narrow sphere during locomotion. However, the pattern of these movements delineates a certain frame within the space, and provides not only visual effects but also relevance tomovement itself. Also, critically dividing and organizing this sphere is what is realized into this tangible indoor space. This study recognized importance of human being as a core of making indoor space and brought out experimental approach on relationship human with space, and visually perceptual standpoint. And this presented the recent possibility of action and attitude though sight and walking by arranging space on the basis of modern artists' perception of human body.

• 대한인간공학회지
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• 제19권1호
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• pp.77-90
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• 2000

The aim of this study is to develop and evaluate an efficient camera calibration method for vision-based head tracking. Tracking head movements is important in the design of an eye-controlled human/computer interface. A vision-based head tracking system was proposed to allow the user's head movements in the design of the eye-controlled human/computer interface. We proposed an efficient camera calibration method to track the 3D position and orientation of the user's head accurately. We also evaluated the performance of the proposed method. The experimental error analysis results showed that the proposed method can provide more accurate and stable pose (i.e. position and orientation) of the camera than the conventional direct linear transformation method which has been used in camera calibration. The results of this study can be applied to the tracking head movements related to the eye-controlled human/computer interface and the virtual reality technology.

• International Journal of Internet, Broadcasting and Communication
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• 제12권4호
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• pp.93-101
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• 2020

Shipyards are potential environments for using IoT services, sensor networks, and delay tolerant networks. Simulations of those services and networks strongly rely on human mobility models. Results obtained with an unrealistic model may not reflect the true performance of applications, protocols, and algorithms in a shipyard. A lot of synthetic models for human movements have been studied but most of them are generic and focus on the daily movements of humans on city scales. Nevertheless, workers in shipyards have unique movement characteristics such as movement speed, pause time, and attractions places. For instance, workers usually move to some places, where they work, and rarely move to other places in the factory. Movement characteristics of workers not only depend on workers but also on tasks, which they do. For instance, workers, who paint ships, have similar movement speed and pause time. Hence, in this paper, human movements in shipyards are studied. We propose a new human mobility model called the human mobility mode in shipyards (MIS). In MIS, workers are classified into multiple types. Movement characteristics of a worker are similar to other workers in the same type. Based on the visiting probability, workers have some places, where they frequently visits, and some places, where they rarely visit. We analyze real mobility traces and studie to achieve human movement characteristics from real traces. The results show that MIS provides a well-match to the movement characteristic from real traces.