• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.186-192
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• 2009

In this paper, we represent the recognition method for human frontal upper body pose. In HCI(Human Computer Interaction) and HRI(Human Robot Interaction) when a interaction is established the human has usually frontal direction to the robot or computer and use hand gestures then we decide to focus on human frontal upper-body pose, The two main difficulties are firstly human pose is consist of many parts which cause high DOF(Degree Of Freedom) then the modeling of human pose is difficult. Secondly the matching between image features and modeling information is difficult. Then using Pictorial Model we model the human main poses which are mainly took the space of frontal upper-body poses and we recognize the main poses by making main pose database. using determined main pose we used the model parameters for particle filter which predicts the posterior distribution for pose parameters and can determine more specific pose by updating model parameters from the particle having the maximum likelihood. Therefore based on recognizing main poses and tracking the specific pose we recognize the human frontal upper body poses.

• Korean Journal of Psychosomatic Medicine
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• v.18 no.1
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• pp.40-47
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• 2010

Objectives：Body image is closely related to self-esteem and weight-control related behaviors. In particular, relationship between two factors would be stronger in female adolescents. False recognition on body image and weight can be a risk factor of eating disorder, depression, and suicidal ideation. This study aimed to examine the effects of body image and eating disorders on developing depressive symptoms and suicidal ideation in female adolescents. Methods：Two hundred thirty nine students of a Girls' Commercial High School in Seoul were recruited. Eating Attitude Test for Korean Adolescents, Self-Esteem Scales, Impulsiveness Scale, Beck's Depression Inventory and Beck's Suicidal Ideation Scale were used to measure eating attitude and severity of psychiatric symptoms. Results：Among 239 subjects, the estimated risk group of eating disorders was 10%(n=24). They experienced more depressive symptoms than the control group. The bigger discrepancy in current and ideal body mass index was significantly related with higher depressive mood, suicidal idea, abnormal eating habits and lower self-esteem. Discrepancy between current and idea BMI was the most meaningful predictive factor about depression and suicidal thoughts by linear regression analysis. Conclusion：In spite of normal weight range of enrolled subjects, they experienced significant depressive mood, suicide thoughts and lower self-esteem associated with the discrepancy of their own subjective body image and current body mass index. Hence educational approach regarding normal body image and healthy weight control is needed for their mental health and preventing eating disorder.

• Journal of the Korea Society of Computer and Information
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• v.21 no.2
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• pp.17-23
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• 2016

NUI is a motion interface. It uses the body of the user without the use of HID device such as a mouse and keyboard to control the device. In this paper, we use a Pi Camera and sensors connected to it with small embedded board Raspberry Pi. We are using the OpenCV algorithms optimized for image recognition and computer vision compared with traditional HID equipment and to implement a more human-friendly and intuitive interface NUI devices. comparison operation detects motion, it proposed a more advanced motion sensors and recognition systems fused connected to the Raspberry Pi.

• Smart Media Journal
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• v.11 no.1
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• pp.46-57
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• 2022

In this paper, multi-region based Radial Graph Convolutional Network (MRGCN) algorithm which can perform end-to-end action recognition using the optical flow and gradient of input image is described. Because this method does not use information of skeleton that is difficult to acquire and complicated to estimate, it can be used in general CCTV environment in which only video camera is used. The novelty of MRGCN is that it expresses the optical flow and gradient of the input image as directional histograms and then converts it into six feature vectors to reduce the amount of computational load and uses a newly developed radial type network model to hierarchically propagate the deformation and shape change of the human body in spatio-temporal space. Another important feature is that the data input areas are arranged being overlapped each other, so that information is not spatially disconnected among input nodes. As a result of performing MRGCN's action recognition performance evaluation experiment for 30 actions, it was possible to obtain Top-1 accuracy of 84.78%, which is superior to the existing GCN-based action recognition method using skeleton data as an input.

• Journal of the East Asian Society of Dietary Life
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• v.21 no.4
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• pp.587-599
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• 2011

The purpose of this study was to examine self-perception of body image and dieting behaviors by gender among high school students. The data were collected by a self-administered questionnaire during April, 2010, and analyzed by SPSS Windows V.18.0. The results were as follows. First, many respondents showed a desire to be underweight and regarded themselves as overweight, even though they had a normal BMI. Second, female respondents showed a higher level of concern about diet than male respondents. Third, male respondents received information about diet mostly from their family or friends, whereas female respondents received information from blogs, mini-homepages, or Kin-search on the Internet. Finally, female respondents showed a higher level of practice for fasting therapy than male respondents, whereas male respondents showed a higher level of practice for food therapy, drug therapy, oriental medicine therapy, and steam bath therapy. Therefore, high school should educate students to get right recognition and knowledge of diet.

• Journal of the Korea Convergence Society
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• v.11 no.10
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• pp.207-212
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• 2020

This study analyzes the Soju(Korean alcohol) advertisement image, which is relatively easy to interpret subjectively, among sexual appeal advertisements that stimulate consumers' curiosity, where the image is verified through AOI (area of interest) 3 areas (face, body, product), and eye-tracking, one of the psychophysiological indicators. The result of the analysis reveals that visual attention, the interest in the advertising model, was higher in the face than in the body shape. Contrary to the prediction that men would be more interested in body shape than women, both men and women showed higher interest in the face than a body. Besides, it was derived that recognition and recollection of the product were not significant. This study is significant in terms of examining the pattern of visual attention such as the gaze point and gaze time of male and female consumers on sexual appeal advertisements. In further, the study looks forward to bringing a positive influence to the soju advertisement image by presenting the expression method that the soju advertisement image should pursue as well as the appropriate marketing direction.

• Journal of Biosystems Engineering
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• v.28 no.1
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• pp.65-76
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• 2003

The analysis of cow body parameters is important to provide some useful information fur cow management and cow evaluation. Present methods give many stresses to cows because they are invasive and constrain cow postures during measurement of body parameters. This study was conducted to develop the stereo vision system fur non-invasive analysis of cow body features. Body feature parameters of 16 heads at two farms(A, B) were measured using scales and nineteen stereo images of them with walking postures were captured under outdoor illumination. In this study, the camera calibration and inverse perspective transformation technique was established fer the stereo vision system. Two calibration results were presented for farm A and fm B, respectively because setup distances from camera to cow were 510 cm at farm A and 630cm at farm B. Calibration error values fer the stereo vision system were within 2 cm for farm A and less than 4.9 cm for farm B. Eleven feature points of cow body were extracted on stereo images interactively and five assistant points were determined by computer program. 3D world coordinates for these 15 points were calculated by computer program and also used for calculation of cow body parameters such as withers height. pelvic arch height. body length. slope body length. chest depth and chest width. Measured errors for body parameters were less than 10% for most cows. For a few cow. measured errors for slope body length and chest width were more than 10% due to searching errors fer their feature points at inside-body positions. Equation for chest girth estimated by chest depth and chest width was presented. Maximum of estimated error fur chest girth was within 10% of real values and mean value of estimated error was 8.2cm. The analysis of cow body parameters using stereo vision system were successful although body shape on the binocular stereo image was distorted due to cow movements.

• Korean Journal of Community Nutrition
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• v.6 no.4
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• pp.577-591
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• 2001

This study was carried out to investigate the difference of the body image recognition, food habits, food behaviors and nutrient intake according to the obesity index(underweight-, normal-, obese group) in children(aged 10.8 ys, 47 boys, 33 girls). Subjects were eva1uated based an anthrofometric measurement and questionnaries including food record diary in Changwon. The results are summarized as follows. The weight, BMI, body fat, waist circumference, hip circumference and birth weight except height showed a significant difference between the three groups(p<0.001). The waist and hip circumference showed the possibility of being a predictor of obesity in children. The children's obesity was related to mother's weight(p<0.01), but not to father's. Ninety percent of the obese group, 47.8% of the normal group, and 37.8% of the underweight group preferred a thinner figure than their current status. The underweight group did more exercise regularly than the other groups. The underweight and obese groups had more irregular meal times and foster eating habits compared to the normal group. Most of subjects(89.9%) had an overeating habit, and tole ratio of the overeating habit increased with obesity. Fifty five percent of the subjects clad the habit of skipping meals, mainly breakfast. 46.8% of the subjects ate snacks more than twice per a day, the underweight and obese groups had snacks more of than the normal group. The preferred snack was 'cookies'and 'fruits ＆ juices'. 53.8% of the subjects had a prejudice for special food(especially 'pulses'(37.9%) and 'vegetables'(31.0%)). The assessment scores of food behaviors was relatively low in most of the subjects. Most nutrient intakes, except vitamin B$_1$, C and phosphate, were lower than those of Korean RDA. The nutrient intake of the normal group was higher than the underweight and obese groups. The results of this study showed some nutritional problems, which indicates the need for nutritional management for the children. To educate children, who are able to change their food habits and lifestyle, each means to help healthy growth and to help them become healthy adults.

• International journal of advanced smart convergence
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• v.8 no.1
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• pp.126-132
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• 2019

Creative thinking appears even before it is expressed in language, and its existence is revealed through emotion, intuition, image and body feeling before logic or linguistics rules work. In this study, Lego is intended to present experimental child interactive content that is applied with a computer vision based on image processing techniques. In the case of infants, the main purpose of this content is the development of hand muscles and the ability to implement imagination. The purpose of the analysis algorithm of the OpenCV library and the image processing using the 'VVVV' that is implemented as a 'Node' in the midst of perceptual changes in image processing technology that are representative of object recognition, and the objective is to use a webcam to film, recognize, derive results that match the analysis and produce interactive content that is completed by the user participating. Research shows what Lego children have made, and children can create things themselves and develop creativity. Furthermore, we expect to be able to infer a diverse and individualistic person's thinking based on more data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.212-215
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• 2022

In the era of so-called digital transformation today, the need for the construction and utilization of big data in various fields has increased. Today, a lot of data is produced and stored in a digital device and media-friendly manner, but the production and storage of data for a long time in the past has been dominated by print books. Therefore, the need for Optical Character Recognition (OCR) technology to utilize the vast amount of print books accumulated for a long time as big data was also required in line with the need for big data. In this study, a system for digitizing the structure and content of a document object inside a scanned book image is proposed. The proposal system largely consists of the following three steps. 1) Recognition of area information by document objects (table, equation, picture, text body) in scanned book image. 2) OCR processing for each area of the text body-table-formula module according to recognized document object areas. 3) The processed document informations gather up and returned to the JSON format. The model proposed in this study uses an open-source project that additional learning and improvement. Intelligent OCR proposed as a system in this study showed commercial OCR software-level performance in processing four types of document objects(table, equation, image, text body).