• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권5호
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• pp.1856-1869
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• 2015

This paper addresses the issues of 3D human activity detection, tracking and recognition from RGB-D video sequences using a feature structured framework. During human tracking and activity recognition, initially, dense depth images are captured using depth camera. In order to track human silhouettes, we considered spatial/temporal continuity, constraints of human motion information and compute centroids of each activity based on chain coding mechanism and centroids point extraction. In body skin joints features, we estimate human body skin color to identify human body parts (i.e., head, hands, and feet) likely to extract joint points information. These joints points are further processed as feature extraction process including distance position features and centroid distance features. Lastly, self-organized maps are used to recognize different activities. Experimental results demonstrate that the proposed method is reliable and efficient in recognizing human poses at different realistic scenes. The proposed system should be applicable to different consumer application systems such as healthcare system, video surveillance system and indoor monitoring systems which track and recognize different activities of multiple users.

• The KIPS Transactions:PartB
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• 제18B권5호
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• pp.305-314
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• 2011

Research into the visual perception of human emotion to recognize an intention has traditionally focused on emotions of facial expression. Recently researchers have turned to the more challenging field of emotional expressions through body posture or activity. Proposed work approaches recognition of basic emotional categories from body postures using neural model applied visual perception of neurophysiology. In keeping with information processing models of the visual cortex, this work constructs a biologically plausible hierarchy of neural detectors, which can discriminate 6 basic emotional states from static views of associated body postures of activity. The proposed model, which is tolerant to parameter variations, presents its possibility by evaluating against human test subjects on a set of body postures of activities.

• The Journal of the Korea Contents Association
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• 제11권12호
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• pp.619-628
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• 2011

Normally vision-based 3D human pose recognition technology is used to method for convey human gesture in HCI(Human-Computer Interaction). 2D pose model based recognition method recognizes simple 2D human pose in particular environment. On the other hand, 3D pose model which describes 3D human body skeletal structure can recognize more complex 3D pose than 2D pose model in because it can use joint angle and shape information of body part. In this paper, we describe a development of interactive game contents using pose recognition interface that using 3D human body joint information. Our system was proposed for the purpose that users can control the game contents with body motion without any additional equipment. Poses are recognized comparing current input pose and predefined pose template which is consist of 14 human body joint 3D information. We implement the game contents with the our pose recognition system and make sure about the efficiency of our proposed system. In the future, we will improve the system that can be recognized poses in various environments robustly.

• Proceedings of the KIEE Conference
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.187-189
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• 2004

This paper presents the system widely used for extraction of human body recognition system in the field of bio-metric identification. The Human body recognition system is used in many fields. This biological is appled to the human recognition in banking and the access control with security. The important algorithm of the identification software usese hand lines and hand shape geometry. We used the simple algorithm and recognizing the person by their hand image from the input camera. The geometrical characteristics in hand shape such as length of finger to whole hand length thickness of finger to length, etc are used.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권11호
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• pp.2839-2852
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• 2013

Context-awareness is an essential part of ubiquitous computing, and over the past decade video based activity recognition (VAR) has emerged as an important component to identify user's context for automatic service delivery in context-aware applications. The accuracy of VAR significantly depends on the performance of the employed human body segmentation algorithm. Previous human body segmentation algorithms often engage modeling of the human body that normally requires bulky amount of training data and cannot competently handle changes over time. Recently, active contours have emerged as a successful segmentation technique in still images. In this paper, an active contour model with the integration of Chan Vese (CV) energy and Bhattacharya distance functions are adapted for automatic human body segmentation using depth cameras for VAR. The proposed technique not only outperforms existing segmentation methods in normal scenarios but it is also more robust to noise. Moreover, it is unsupervised, i.e., no prior human body model is needed. The performance of the proposed segmentation technique is compared against conventional CV Active Contour (AC) model using a depth-camera and obtained much better performance over it.

• Journal of Korean Home Economics Education Association
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• 제10권1호
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• pp.17-27
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• 1998

The purpose of this study was to investigate the recognition of body shape, the difference between self-evaluated obesity and obesity index of RBW, and attitude toward weight control of middle students. The questionnaires were completed by 195 male and 189 female students of liveing in Yongwol county. The average stature of the boys is 166.97$\pm$6.21cm, the girls is 158.13$\pm$5.83cm, and the average weight of the boys is 57.97$\pm$12.39kg, the girls is 52.88$\pm$8.35kg. 2. In the present body structure of them, the underweight structure is 6.0%, the normal weight structure is 87.2%, and the overweight structure is 6.7%. In the recognition of their own body structures, there are meaningful differences between boys and girls. 3. In the contentment degree of the present body structure of their own, the underweiht structure is much more satisfied with it.(p〈0.001) It shows a meaningful difference between boys and girls. 25.6% boys are satisfied with their own body structures, and 7.4% girls are satisfied with it.(p〈0.001) 4. In the interest degree about the weight's control, 87.1% is interested in it, it is lower in the underweight structure. 88.0% girls and 77.4% boys are interested in the weight's control. There is a meaningful difference between boys and girls, too.(p〈0.001) Each of the weight groups has differences in a experienced or experiencing for the weight's control. 5. The recognition degree of the present body structure showed the meaningful positive relation to the contentment degree of the present body structure and the weight's control.(p〈0.001)

• Journal of the Korean Dietetic Association
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• 제6권2호
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• pp.171-178
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• 2000

The purpose of this study was to obtain basic data of nutrition education for obese children in Seoul and to examine dietary habits, dietary behaviors, and body image recognition before and after nutrition education. A convenience sample of 69(male : 54, female : 15) obese children was selected from "98 Children Nutrition Camp" in Seoul. The survey design employed a structured questionnaires. The results of this study were summarized as follows ; 1. Anthropometric parameters such as height, weight were measured in 69 obese subjects of age 10~12. 2. Effects of nutrition knowledge were gained by dietary habits, dietary behaviors and body image recognition. 3. Comparison of nutrition knowledge scores for obese children was to obtain basic data of effects for nutrition education.

• Smart Media Journal
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• 제5권3호
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• pp.49-53
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• 2016

Related researches are progressing that method of non-contact method using the electromagnetic field on the human body by detecting the motion recognition signal is the limitations of time and space, so less than the existing systems. In this paper, we designed the circuit system that can implement the hardware that can detect the electric field signal of the human body non-contact method to increase the recognition rate to screen this digital waveform. The PCB design Used to automatically increase of composition of the circuit and the linkage of the comparator digital waveform with circuit simulation of the system. At same time for evaluate the characteristics of the whole circuit system.

• Korean Journal of Community Nutrition
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• 제10권6호
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• pp.825-834
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• 2005

This study was to investigate the effects of the body fat $\%$ on life styles and self-recognition of health conditions in hotel culinary college students. This survey was conducted using the questionnaires for 144 students (110 males, 34 female) in Hongseung-located college. More exercise time and less frequency of alcoholic beverage they intake, lowered their body fat $\%$. Males did stronger exercise and had lower body fat $\%$ than females. The stronger exercise they did, the lower body fat $\%$ they had, and were more satisfied with their present weight. Since they had more alcoholic beverage, they smoked more. Less smoking, more abdominal obesity they were. The less satisfaction with their body weights, the higher body fat $\%$ they had. The obese less were content with their weights. More recognition of obese shape, higher body fat $\%$ they had and abdominal obesity they were. Female had higher body fat $\%$ and were more abdominal obesity, did weak action, less smoke and weak exercise than male. Higher body fat $\%$ they had, more abdominal obesity they were. The more part time jobs they had, they did not smoke or were not satisfied with their body weights. Female students in culinary arts division had higher body fat $\%$ and were dissatisfied with their body weights and did less exercise or subnormal exercises. (Korean J Communty Nutrition 10(6) : $825\∼834$, 2005)

• Journal of Korea Game Society
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• 제11권6호
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• pp.103-113
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• 2011

In this paper, we propose gesture recognition based 3D Serious Games to prevent dementia. These games are designed to enhance the effect of preventing dementia by helping increase brain usage and physical activities of users by the entire body gesture recognition. The existing cameras used for gesture recognition technology are limited in terms of recognition ratio and operation range. For more stable recognition of the body gestures, we recognized users with a 3D depth camera, obtained joint data of users, and analyzed joint motions to recognize gestures of the body. Game contents were designed to practice memory, reasoning, calculation, and spatial recognition focusing on the atrophy of brain cells as a major cause of dementia. Game results of each user were saved and analyzed to measure how their recognition skills improved.