• Science of Emotion and Sensibility
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• v.5 no.4
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• pp.1-10
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• 2002

A web based virtual try-on provides customers a more enjoyable shopping experience that visualize clothes on personal mannequin. The researchers compared virtual fitting models which were developed in 2000 at Korea and in 2000 and 2002 at U.S. The results of this study as follows: The information about user's body size was required to input for selection of a virtual fitting model. 7 to 19 different body size, shape, and face features including weight and height were needed for visualizing virtual fitting model. The body type of the U.S virtual fitting model(My virtual model) was selected by front view silhouette for women, and by shoulder width and midriff silhouette for men. The more detailed information was required for developing Korean virtual fitting model. The additional body size information required in the site were leg and arm lengths, waist length, and thigh and ankle circumferences. The body proportion of Korean cyber personal mannequin was longer and narrower than the U.S cyber personal mannequin. It was recommended that standardized body length, width, and depth proportions calculated from national anthropometric data must be applied for developing Korean virtual fitting model. With application of more detailed information on face feature and advanced graphic image technology the 'My virtual model in 2002 resembled the human body shape of various race.

• Journal of Fashion Business
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• v.16 no.1
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• pp.103-120
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• 2012

The study aimed to evaluate the appearance of the men's work clothes jumpers developed to suggest the prototype work clothes jumper patterns by using the 3-D clothing simulation technology. The 3-D simulated clothing images considered the upper body features of men in the age range between 20 and 59 in South Korea. A questionnaire survey conducted previously suggested a basic jumper style with shirt collar and snap opening cuffs for the heavy industry workers; and discomforting parts of the work clothes jumper of the subject workers have been referred to for the experimental jumper appearance test. Besides, defining the measurements of men's upper bodies enabled to generate the men's 3-D virtual models representing each age group's average body feature. The significant body measurement factors for men's 3-D body modeling and jumper pattern-making were stature for the height factor; chest, waist and hip circumferences for the circumference factor; waist back, hip and arm lengths and interscye front/back for the length factor; and back neck breadth for the breadth factor and armscye and scye depths for the depth factor. The men's body measurements of 30's were implemented to three experimental jumper pattern-making methods, i.e. the 1st method using the relations based on stature and chest circumference; the 2nd method using the direct body measurements; and the 3rd method adopting the maximum ease amount of given body measurements whether relations or direct measurements except the direct measurement of scye depth. A comparison among the three experimental jumpers' simulated images highlighted that the appropriate ease amount of the jumper gained higher scores in terms of the jumpers' front, side, back and sleeve parts and the total silhouettes. Therefore the 3rd experimental jumper was finally selected for the heavy industry workers.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.4
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• pp.159-166
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• 2020

The IBC (Intra-Body Communication) benefits from a wireless communication system for exchanging various kinds of digital information through wearable electronic devices and sensors. The IBC using the human body as the transmission channel allows wireless communication without the transmitting radio frequency waves to the air. This paper discusses the results of experiments on electrostatic coupling IBC based on FSK (Frequency Shift Keying) and 1 bit error correction. We implemented FSK communication and 1 bit error correction algorithm using the MCU boards and aluminum tape electrodes. The transmitter modulates digital data using 50% duty square wave as carrier signal and transmits data through human body. The receiver performs ADC (Analog to Digital Conversion) on carrier signal from human body. In order to figure out the frequency of carrier signal from ADC results, we applied zero-crossing algorithm which is used to detect the edge characteristic in computer vision. Experiment results shows that digital data modulated as square wave can be successfully transmitted through human body by applying the proposed architecture of a 1ch GPIO as a transmitter and 1ch ADC for as a receiver. Also, this paper proposes 1 bit error correction technique for reliable IBC. This technique performs error correction by utilizing the feature that carrier signal has 50% duty ratio. When 1 bit error correction technique is applied, the byte error rate at receiver side is improved around 3.5% compared to that not applied.

• Journal of KIISE:Software and Applications
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• v.36 no.10
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• pp.836-850
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• 2009

Human posture recognition has attracted tremendous attention in ubiquitous environment, performing arts and robot control so that, recently, many researchers in pattern recognition and computer vision are working to make efficient posture recognition system. However the most of existing studies is very sensitive to human variations such as the rotation or the translation of body. This is why the feature, which is extracted from the feature extraction part as the first step of general posture recognition system, is influenced by these variations. To alleviate these human variations and improve the posture recognition result, this paper presents 3D Star Skeleton and Principle Component Analysis (PCA) based feature extraction methods in the multi-view environment. The proposed system use the 8 projection maps, a kind of depth map, as an input data. And the projection maps are extracted from the visual hull generation process. Though these data, the system constructs 3D Star Skeleton and extracts the rotation invariant feature using PCA. In experimental result, we extract the feature from the 3D Star Skeleton and recognize the human posture using the feature. Finally we prove that the proposed method is robust to human variations.

• Journal of the Korea Fashion and Costume Design Association
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• v.17 no.3
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• pp.13-27
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• 2015

The purpose of this study is to understand the general process from textile design till fashion design and to understand the relation between the body structure by using the x-ray technique. The research method was to see background of the anatomic feature and human skeletal X-ray projection through historical aspect of publications, the Internet, and paper. In terms of production, in order to present a design that takes into account the unique silhouette of the human body without distorting the shape of the human skeleton, X-ray images that were reconstituted using a computer graphic tool (Photoshop CS) were reproduced into the fabric as intense images through the digital Textile Printing technique that is capable of expressing fine and delicate details, and applied into the design. An original design was developed that emphasized the impression of the human body being projected and the shape of the human skeleton realistically expressed in terms of silhouette and detail. The results are as follows: First, Body has a anatomic formative characteristic and its formativeness becomes as a great motive for the artistic expression and thereby it becomes more unique and available for new design expression. Second, Using the 'body frame' as the motive of the research, there's mainly tried to make an unique expression. Third, according to reconstructing human skeletal X-ray projection by using Adobe Photoshop CS2, it can be expressed strong and unique design. Forth, DTP which is being used as an essential technique, expresses the body frame realistically and being used the special type of functional product and silk. Likewise by discovering the diverse formativeness of our body frame and reflecting the sense of humanity into the pieces there's been able to make and develop an unique fashion design. I sincerely hope there is a hug progress in this research in this area.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.5
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• pp.63-71
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• 2008

In this paper, we propose a color based hierarchically propagated particle filter that extends the color based particle filter into the articulated upper body tracking. Since color feature is robust to partial occlusion and rotation, the color based particle filter is widely used for object tracking. However, in articulated body tacking, it is not desirable to use the traditional particle filter because the dimension of the state vector usually is high and thus, many samples are required for robust hacking. To overcome this problem, we use a hierarchical tracking method for each body part based on the blown body part. By using a hierarchical tracking method, we can reduce the number of samples for robust tracking in the cluttered environment. Also for human pose recognition, we classify the human pose into eight categories using Support Vector Machine(SVM) according to the angle between upper- arm and fore-arm. Experimental results show that our proposed method is more efficient than the traditional particle filter.

• Journal of IKEEE
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• v.24 no.1
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• pp.120-126
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• 2020

We present a user recognition method using human body impulse response signals. The body compositions vary from person to person depending on the portion of water, muscle, and fat. In the body communication study, the body has been interpreted circuit models using capacitance and resistances, and its characteristics are determined by the body compositions. Therefore, the individual body channel is unique and can be used for user recognition. In this paper, we applied pseudo impulse signals to the left hand and recorded received signals from the right hand. The empirical mode decomposition (EMD) method removed noise from the received signals and 10 peak values are extracted. We set the differences between peak amplitudes as a key feature to identify individuals. We collected data from 6 subjects and achieved accuracy of 97.71% for the user recognition application.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.4 s.316
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• pp.86-92
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• 2007

A discrete dynamic model for tracking feature points in 2D images is developed. Conventional snake approaches deform a contour to lock onto features of interest within an image by finding a minimum of its energy functional, composed of internal and external forces. The neighborhood around center snaxel is a space matrix, typically rectangular. The structure of the model proposed in this paper is a set of connected vertices. Energy model is designed for its local minima to comprise the set of alternative solutions available to active process. Block on tracking is one dimension, line type. Initial starting points are defined to the satisfaction of indent states, which is then automatically modified by an energy minimizing process. The track is influenced by curvature constraints, ascent/descent or upper/lower points. The advantages and effectiveness of this layer approach may also be applied to feature points tracking of digital image whose pixels have one directional properties with high autocorrelation between adjacent data lines, vertically or horizontally. The test image is the ultrasonic carotid artery image of human body, and we have verified its effect on intima/adventitia starting points tracking.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.322-327
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• 2007

Researchers in the field of psychology used Electroencephalographic (EEG) to record activities of human brain lot many years. As technology develope, neural basis of functional areas of emotion processing is revealed gradually. So we measure fundamental areas of human brain that controls emotion of human by using EEG. Hands gestures such as shaking and head gesture such as nodding are often used as human body languages for communication with each other, and their recognition is important that it is a useful communication medium between human and computers. Research methods about gesture recognition are used of computer vision. Many researchers study emotion recognition method which uses one of physiological signals and gestures in the existing research. In this paper, we use together physiological signals and gestures for emotion recognition of human. And we select the driver emotion as a specific target. The experimental result shows that using of both physiological signals and gestures gets high recognition rates better than using physiological signals or gestures. Both physiological signals and gestures use Interactive Feature Selection(IFS) for the feature selection whose method is based on a reinforcement learning.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1431-1445
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• 2022

We construct a deep neural network model named ECGResNet. This model can diagnosis diseases based on 12-lead ECG data of eight common cardiovascular diseases with a high accuracy. We chose the 16 Blocks of ResNet50 as the main body of the model and added the Squeeze-and-Excitation module to learn the data information between channels adaptively. We modified the first convolutional layer of ResNet50 which has a convolutional kernel of 7 to a superposition of convolutional kernels of 8 and 16 as our feature extraction method. This way allows the model to focus on the overall trend of the ECG signal while also noticing subtle changes. The model further improves the accuracy of cardiovascular and cerebrovascular disease classification by using a fully connected layer that integrates factors such as gender and age. The ECGResNet model adds Dropout layers to both the residual block and SE module of ResNet50, further avoiding the phenomenon of model overfitting. The model was eventually trained using a five-fold cross-validation and Flooding training method, with an accuracy of 95% on the test set and an F1-score of 0.841.We design a new deep neural network, innovate a multi-scale feature extraction method, and apply the SE module to extract features of ECG data.