• Journal of Biomedical Engineering Research
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• v.24 no.4
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• pp.309-318
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• 2003

In this paper a 6 degree-of-freedom robot was studied for medical purpose. In the past the robot used for industry field was utilized for medical robot but in these days the robot used for rehabilitation. welfare, and service. This system was Proposed for a stroke patient or a patient who can not use one arm. A master-slave system was constructed to exercise either paralysis or abnormal arm using normal arms movement. Study on the human body motion result was applied to calculate a movement range of humans elbow and shoulder. In addition, a force-torque sensor is applied to estimate the rehabilitation extent of the patient in the slave robot. Therefore, the stability of the rehabilitation robot could be improved. By using the rehabilitation robot, the Patient could exercise by himself without any assistance In conclusion. the proposed system and control algorithm were verified by computer simulation and system experiment.

• Smart Media Journal
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• v.5 no.1
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• pp.38-43
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• 2016

As smart environment is spread out in our living environments, the needs of an approach related to Human Computer Interaction(HCI) is increases. One of them is head pose estimation. it related to gaze direction estimation, since head has a close relationship to eyes by the body structure. It's a key factor in identifying person's intention or the target of interest, hence it is an essential research in HCI. In this paper, we propose an approach for head pose estimation with pre-defined several directions by random forest classifier. We use canny edge detector to extract feature of the different facial image which is obtained between input image and averaged frontal facial image for extraction of rotation information of input image. From that, we obtain the binary edge image, and make two accumulated histograms which are obtained by counting the number of pixel which has non-zero value along each of the axes. This two accumulated histograms are used to feature of the facial image. We use CAS-PEAL-R1 Dataset for training and testing to random forest classifier, and obtained 80.6% accuracy.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.1
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• pp.71-81
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• 2011

Due to increased human activities and intensive rainfall events in a watershed, soil erosion and sediment transport have been hot issues in many areas of the world. To evaluate soil erosion problems spatially and temporarily, many computer models have been developed and evaluated over the years. However, it would not be reasonable to apply the model to a watershed if topography and environment are different to some degrees. Also, source codes of these models are not always public for modification. The ArcGIS model builder provides ease-of-use interface to develop model by linking several processes and input/output data together. In addition, it would be much easier to modify/enhance the model developed by others. Thus, simple model was developed to decide soil erosion hot spot areas using ArcGIS model builder tool in this study. This tool was applied to a watershed to evaluate model performance. It was found that sediment yield was estimated to be 13.7 ton/ha/yr at the most severe soil erosion hot spot area in the study watershed. As shown in this study, the ArcGIS model builder is an efficient tool to develop simple models without professional programming abilities. The model, developed in this study, is available at http://www.EnvSys.co.kr/~sateec/toolbox for free download. This tool can be easily modified for further enhancement with simple operations within ArcGIS model builder interface. Although very simple soil erosion and sediment yield were developed using model builder and applied to study watershed for soil erosion hot spot area in this study. The approaches shown in this study provides insights for model development and code sharing for the researchers in the related areas.

• Korean Institute of Interior Design Journal
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• v.15 no.3 s.56
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• pp.83-91
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• 2006

Our human society is rapidly changing into the world of advanced visual information with the development of image industry, the advent of satellite and terrestrial DMB, and the opening of Ubiquitous era. Like this, we are living in the space of overflowing media contents. Jean Baudrillad anticipated that the influential power of image would dominate our reality in 'Simulation'. Noticing the indication of our time, which is organized by various information media including the mass media, Baudrillad predicted that the 21st century would be an era of symbol and image due to the development of television, computer, and internet. This paper attempts to find the physical and conceptual peculiarities of the space change according to the use of display, by analyzing SF films, where future daily life is a major setting, under the judgement that the exploration of space change is significant. Through findings, it tries to lead the visual expansion, which recognizes display as space itself rather than object of space and changes unmoving space into moving space, and suggest the future space design by using digital space. It suggests case studies, which use digital display in the real space, as a study method and it examines the features, influences, and roles of digital display through investigating literatures and cases. In addition, it attempts to find a correlation of digital display and space by selecting films, which can give the affluent resources of analysis on the digital display among SF films. Therefore, it will come to a conclusion that space change should be dealt with in the space design.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.53-60
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• 2009

The vision-based driver fatigue detection is one of the most prospective commercial applications of facial expression recognition technology. The facial feature tracking is the primary technique issue in it. Current facial tracking technology faces three challenges: (1) detection failure of some or all of features due to a variety of lighting conditions and head motions; (2) multiple and non-rigid object tracking; and (3) features occlusion when the head is in oblique angles. In this paper, we propose a new active approach. First, the active IR sensor is used to robustly detect pupils under variable lighting conditions. The detected pupils are then used to predict the head motion. Furthermore, face movement is assumed to be locally smooth so that a facial feature can be tracked with a Kalman filter. The simultaneous use of the pupil constraint and the Kalman filtering greatly increases the prediction accuracy for each feature position. Feature detection is accomplished in the Gabor space with respect to the vicinity of predicted location. Local graphs consisting of identified features are extracted and used to capture the spatial relationship among detected features. Finally, a graph-based reliability propagation is proposed to tackle the occlusion problem and verify the tracking results. The experimental results show validity of our active approach to real-life facial tracking under variable lighting conditions, head orientations, and facial expressions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.603-607
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• 2004

The vision-based driver fatigue detection is one of the most prospective commercial applications of facial expression recognition technology. The facial feature tracking is the primary technique issue in it. Current facial tracking technology faces three challenges: (1) detection failure of some or all of features due to a variety of lighting conditions and head motions; (2) multiple and non-rigid object tracking and (3) features occlusion when the head is in oblique angles. In this paper, we propose a new active approach. First, the active IR sensor is used to robustly detect pupils under variable lighting conditions. The detected pupils are then used to predict the head motion. Furthermore, face movement is assumed to be locally smooth so that a facial feature can be tracked with a Kalman filter. The simultaneous use of the pupil constraint and the Kalman filtering greatly increases the prediction accuracy for each feature position. Feature detection is accomplished in the Gabor space with respect to the vicinity of predicted location. Local graphs consisting of identified features are extracted and used to capture the spatial relationship among detected features. Finally, a graph-based reliability propagation is proposed to tackle the occlusion problem and verify the tracking results. The experimental results show validity of our active approach to real-life facial tracking under variable lighting conditions, head orientations, and facial expressions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.934-937
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• 2010

In this paper, we did pursue the embodiment of a mouse pointing system which help the handicapped and people of not familiar with using electronics use electronic devices easily. Speech Recognition and 3-axis acceleration sensors in conjunction with a headset, a new mouse pointing system is constructed. We used speaker dependent system module which are generating the BCD code by recognizing human voices because it has high recognition rate rather than speaker independent system. Head-set mouse system is organized by 3-axis accelerometer, sound recognition module and TMS320F2812 processor. The main controller, TMS320F2812 DSP-processor is communicated with main computer by using SCI communications. The system is operated by Visual Basic in PC.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.10
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• pp.1314-1319
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• 2018

The current TW3 - based maximum height prediction technique used in KMAA(Korean Medical Academy of Auxology) is manual and subjective, and it requires a lot of time and effort in the medical treatment, while the interest in the child's growth is very high. In addition, the technique of classifying images using deep learning, especially convolutional neural networks, is used in many fields at a more accurate level than the human eyes, also there is no exception in the medical field. In this paper, we introduce a TW3 algorithm using deep learning, that uses the convolutional neural network to predict the growth level of the left hand bone, to predict the maximum height of child and youth in order to increase the reliability of predictions and improve the convenience of the doctor.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.3
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• pp.34-40
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• 2003

The paper presents a method to detect dissolve shots of video scene change detections in an MPEG compressed domain. The proposed algorithm uses color-R DCT coefficients of Ⅰ, P-frames for a fast operation and accurate detection and a minimum decoding process in MPEG sequences. The paper presents a method to detect dissolve shot for three-dimensional visualization and analysis of Image in order to recognize easily in computer as a human detects accurately shots of scene change. First, Color-R DCT coefficients for 8*8 units are obtained and the features are summed in a row. Second, Four-step analysis are Performed for differences of the sum in the frame sequences. The experimental results showed that the algorithm has better detection performance, such as precision and recall rate, than the existing method using an average for all DC image by performing four step analysis. The algorithm has the advantage of speed, simplicity and accuracy. In addition. it requires less amount of storage.

• The KIPS Transactions:PartA
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• v.16A no.2
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• pp.135-142
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• 2009

With the development of ubiquitous computing technology, the number of HCI applications is increasing, where they utilize various contexts to provide adaptive services to users according to the change of contexts, and also, technologies for collecting various sensor data and generating integrated contexts get more important. However, the research on the collection and integration of multi-sensor data is not sufficient when we consider the various utilization areas of the integrated contexts. In particular, they have some problems to be solved such as duplication of the context data and the high system load. In this paper, we propose an integrated context generation scheme based on Ant Colony System. Proposed scheme generates the context data as a form of XML and avoids the generation of unnecessary context information by detecting the repeated sensor information based on the ant colony system. As a result of detections, we reduce wasted resources and repositories when the integrated context is created. We also reduce the overhead for reasoning.