• The KIPS Transactions:PartB
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• v.18B no.1
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• pp.11-20
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• 2011

Pictorial Structures is known as an effective method that recognizes and tracks human poses. In this paper, the upper body pose is also tracked by PS and a particle filter(PF). PF is one of dynamic programming methods. But Markov chain-based dynamic motion model which is used in dynamic programming methods such as PF, couldn't predict effectively the highly articulated upper body motions. Therefore PF often fails to track upper body pose. In this paper we propose the key pose-based proposal distribution for proper particle prediction based on the similarities between key poses and an upper body silhouette. In the experimental results we confirmed our 70.51% improved performance comparing with a conventional method.

• 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.

• Advances in robotics research
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• v.2 no.2
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• pp.129-140
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• 2018

With the increasing demand for the development of human pose estimation, such as human-computer interaction and human activity recognition, there have been numerous approaches to detect the 2D poses of people in images more efficiently. Despite many years of human pose estimation research, the estimation of human poses with images remains difficult to produce satisfactory results. In this study, we propose a robust 2D human body pose estimation method using an RGB camera sensor. Our pose estimation method is efficient and cost-effective since the use of RGB camera sensor is economically beneficial compared to more commonly used high-priced sensors. For the estimation of upper-body joint positions, semantic segmentation with a fully convolutional network was exploited. From acquired RGB images, joint heatmaps accurately estimate the coordinates of the location of each joint. The network architecture was designed to learn and detect the locations of joints via the sequential prediction processing method. Our proposed method was tested and validated for efficient estimation of the human upper-body pose. The obtained results reveal the potential of a simple RGB camera sensor for human pose estimation applications.

• Journal of the Korean Society of Clothing and Textiles
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• v.38 no.5
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• pp.769-782
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• 2014

This study considers the correlation between model pose and clothes in Patrick Demarchelier's fashion photos as well as expression characteristics. The conclusions of the study are as follows. The type of model pose in Patrick Demarchelier's fashion photos can be categorized into five types: maximized type of upper and lower body part, minimized type of upper and lower body part, maximized type of upper body and minimized type of lower body part, minimized type of upper body and maximized type of lower body part, basic type of upper and lower body part. In case of having examined the correlation between body movement and costume, the clothes in the model pose included in the maximization of the body were formed mainstream by silhouette, which was formed by decorative elements or full drapery. In the model poses included in the reduction of the body, the costume tended to expose many parts of the body to provide a simple or structural silhouette form. The costume was expressed in colorful form and poses assumed without body movements. The expression characteristics of the model poses in Patrick Demarchelier's fashion photos were sensuality, dynamicity, and simplicity. First, sensuality was expressed as feminine sensuality accompanying an erotic mood by naturally emphasizing a woman's breast or leg by reducing the body. Second, dynamicity provided a vividness to the image as if directly living and moving by highlighting the rhythmic aspect of the body. Simplicity aroused the effect of paying attention to clothes or other incidental elements rather than the image expressed by the body of a model by excluding body movement.

• The Journal of the Korea Contents Association
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• v.10 no.8
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• pp.11-17
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• 2010

In this paper, we propose HMM-based upper-body gesture. First, to recognize gesture of space, division about pose that is composing gesture once should be put priority. In order to divide poses which using interface, we used two IR cameras established on front side and side. So we can divide and acquire in front side pose and side pose about one pose in each IR camera. We divided the acquired IR pose image using SVM's non-linear RBF kernel function. If we use RBF kernel, we can divide misclassification between non-linear classification poses. Like this, sequences of divided poses is recognized by gesture using HMM's state transition matrix. The recognized gesture can apply to existent application to do mapping to OS Value.

• 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.

• Korean Journal of Human Ecology
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• v.7 no.3
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• pp.35-48
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• 2004

In this study, by determining lower limb movements which cause significant changes in body surface lines, body parts with the greatest maximum expansion and contraction rate respectively were illustrated in descending order. Using unmarried female university students aged 18 - 24 as subjects, a total of 32 body surface categories (15 body surface lines and 17 body surface segment lines) were measured in one static and 9 movement poses. In particular, expansion and contraction levels and rates were measured and used in the analysis. The analysis first involved the calculation of the average measurement per body part in body surface line in static pose as well as of the average expansion and contraction levels and rates in 9 lower limb movements. Two-way MANOVA and multiple comparison analysis (Tukey) were conducted on movements and individual somatotypes regarding measurement per body part and expansion and contraction rates. Movements which cause measurements of body surface lines differed significantly in body surface line in static pose versus in movement were then identified. Among average expansion and contraction rates in such movements, maximum average expansion and contraction levels, maximum average expansion and contraction rate, and classes of expansion and contraction rate were determined per body part. The results of this study are as follows. First, 5 lower limb movements; F2, F5, F6, F7, F8, which caused significant changes in body surface lines were determined and illustrated in table 4. Second, the levels, rates, and classes of expansion and contraction rate per body part are illustrated in Tables 5 and 6. Body parts with the greatest maximum expansion rate were, in descending order: upper segment of center back leg line, upper segment of inner leg line, middle segment of center front leg line, posterior crotch length, anterior knee girth, anterior thigh girth, center back leg line, girth at crotch height, anterior midway thigh girth, hip girth, anterior crotch length, knee girth, waist girth, inner leg line, thigh girth, and crotch length. Those with the greatest maximum contraction rate were, in descending order: anterior crotch length, upper segment of center front leg line, lower segment of center back leg line, center front leg line, and posterior thigh girth. The maximum expansion rates and maximum contraction rates, which ranged from 2.05 to $35.95\%$ and from -0.20 to $-30.16\%$ respectively, were classified per body part into 4 ABCD classes. The body part with maximum expansion was the upper segment of the center back leg line at vertical body surface line, expanding by $35.95\%$ or 16.03cm in F5 flexion movement. In contrast, the body part with maximum contraction was the anterior crotch length at vertical body surface line, contracting by $-30.16\%$ or -10.54cm in F5 flexion movement. Both, however, were the body parts to expand or contract the most among all horizontal and vertical body surface lines.

• ETRI Journal
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• v.37 no.2
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• pp.406-416
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• 2015

Timing plays a key role in expressing the qualitative aspects of a character's motion; that is, conveying emotional state, personality, and character role, all potentially without changing spatial positions. Temporal editing of locomotion style is particularly difficult for a novice animator since observers are not well attuned to the sense of weight and energy displayed through motion timing; and the interface for adjusting timing is far less intuitive to use than that for adjusting pose. In this paper, we propose an editing system that effectively captures the timing variations in an example locomotion set and utilizes them for style transfer from one motion to another via both global and upper-body timing transfers. The global timing transfer focuses on matching the input motion to the body speed of the selected example motion, while the upper-body timing transfer propagates the sense of movement flow - succession - through the torso and arms. Our transfer process is based on key times detected from the example set and transferring the relative changes of angle rotation in the upper body joints from a timing source to an input target motion. We demonstrate that our approach is practical in an interactive application such that a set of short locomotion cycles can be applied to generate a longer sequence with continuously varied timings.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.359-361
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• 2012

본 논문에서는 깊이영상에서 상반신 포즈 분석을 위하여 원통좌표시스템을 제안한다. 깊이영상에서 포즈 후보 영역을 설정하고, 포즈 후보 영역을 이용하여 카메라로부터 신체 중심점까지의 거리와 신체 특징에 따라 원통좌표계를 설정한다. 그리고 밝기값으로 표현되는 깊이 정보를 이용하여 특징벡터를 추출한다. 추출된 원통좌표계의 특징벡터는 원형의 특징공간에 표현되고 포즈 패턴으로 분류된다. 그리고 포즈 패턴들은 특징벡터들의 평균값을 이용하여 학습되고 미리 정의된 포즈 패턴들과 유클리디언 거리로 비교하여 포즈로 분류된다. 본 논문은 상반신 포즈 후보 영역에 동적인 원통 모델을 적용하여 간단한 연산을 통해 머리와 몸통, 팔을 구분할 수 있도록 효과적인 포즈 정보 추출에 목적을 두고 있다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.4
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• pp.231-235
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• 2011

In these day, the number of people who have an abnormal posture caused by bad habit are increasing. Therefore, people suffer various disease and symptoms. For correcting the posture to cure, we need continuous monitor, expenditure of time and money. In this study, we develop a posture correcting aid system in other to monitor a posture continuously and leads to pose correctly and records postural variation which are attached to the neck and the waist. The devised system showed good potential for the correct posture guide and a cure of postural defect.