• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.173-175
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• 2011

In this paper, we present an user interface which can show some 3D objects at various angles using tracked 3d head position and orientation. In implemented user interface, First, when user's head moves left/right (X-Axis) and up/down(Y-Axis), displayed objects are moved towards user's eyes using 3d head position. Second, when user's head rotate upon an X-Axis(pitch) or an Y-Axis(yaw), displayed objects are rotated by the same value as user's. The results of experiment from a variety of user's position and orientation show good accuracy and reactivity for 3d visualization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9C
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• pp.756-760
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• 2010

This paper is proposed to an novel facial behavior recognition system for driver's fatigue detection. Facial behavior is shown in various facial feature such as head expression, head pose, gaze, wrinkles. But it is very difficult to clearly discriminate a certain behavior by the obtained facial feature. Because, the behavior of a person is complicated and the face representing behavior is vague in providing enough information. The proposed system for facial behavior recognition first performs detection facial feature such as eye tracking, facial feature tracking, furrow detection, head orientation estimation, head motion detection and indicates the obtained feature by AU of FACS. On the basis of the obtained AU, it infers probability each state occur through Bayesian network.

• Korean Journal of Head & Neck Oncology
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• v.17 no.1
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• pp.38-41
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• 2001

Background and Objectives: Thyroid nodules can be diagnosed by FNAB, neck sonography, CT scan, or frozen section with relative accuracy. But some cases, which show no malignancy with those methods, are proved differentiated carcinomas on permanent sections. These false negative results of those diagnostic methods pose difficulties in the surgeon's decision-making process. We analyzed completion thyroidectomies retrospectively in order to make a treatment guideline for thyroid nodules. Materials and Methods: During the last six years, we performed 243 thyroid lobectomies, no evidence of malignancy with preoperative or intraoperative diagnostic methods at the Department of Otolaryngology-Head and Neck Surgery, Ansan and Anam Korea University Hospital. Among these cases, 23 patients (male 6, female 17, mean age 33.4 year old) were proved differentiated thyroid carcinomas on permanent section and we performed completion thyroidectomies. Results: Preoperative FNAB showed seven cases of nodular hyperplasia, 11 cases of follicular adenoma, and five cases of inadequate specimen. Among total 15 cases on frozen section, five cases were nodular hyperplasias, and 10 cases were follicular adenomas. Pathologic results of the permanent section were six cases of papillary cell carcinoma and 17 cases of follicular cell carcinoma. Completion thyroidectomy was performed on all these cases. Conclusion: FNAB and frozen section cannot be sufficient to make the diagnosis of thyroid nodule, we consider that completion thyroidectomy should be performed at the moment with malignant evidence on permanent section.

• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.971-976
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• 2000

In this paper a new method for head gesture recognition is proposed. A the first stage, face image data are transformed into low dimensional vectors by principal component analysis (PCA), which utilizes the high correlation between face pose images. The a self organization map(SM) is trained by the transformed face vectors, in such a that the nodes at similar locations respond to similar poses. A sequence of poses which comprises each model gesture goes through PCA and SOM, and the result is stored in the database. At the recognition stage any sequence of frames goes through the PCA and SOM, and the result is compared with the model gesture stored in the database. To improve robustness of classification, probabilistic relaxation labeling(PRL) is used, which utilizes the contextural information imbedded in the adjacent poses.

• The KIPS Transactions:PartB
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• v.17B no.5
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• pp.355-362
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• 2010

Face tracking is to estimate the motion of a non-rigid face together with a rigid head in 3D, and plays important roles in higher levels such as face/facial expression/emotion recognition. In this paper, we propose an AAM-based face tracking algorithm. AAM has been widely used to segment and track deformable objects, but there are still many difficulties. Particularly, it often tends to diverge or converge into local minima when a target object is self-occluded, partially or completely occluded. To address this problem, we utilize the scale invariant feature transform (SIFT). SIFT is an effective method for self and partial occlusion because it is able to find correspondence between feature points under partial loss. And it enables an AAM to continue to track without re-initialization in complete occlusions thanks to the good performance of global matching. We also register and use the SIFT features extracted from multi-view face images during tracking to effectively track a face across large pose changes. Our proposed algorithm is validated by comparing other algorithms under the above 3 kinds of occlusions.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.83-92
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• 2020

A recent study to determine the fall is focused on analyzing fall motions using a recurrent neural network (RNN), and uses a deep learning approach to get good results for detecting human poses in 2D from a mono color image. In this paper, we investigated the improved detection method to estimate the position of the head and shoulder key points and the acceleration of position change using the skeletal key points information extracted using PoseNet from the image obtained from the 2D RGB low-cost camera, and to increase the accuracy of the fall judgment. In particular, we propose a fall detection method based on the characteristics of post-fall posture in the fall motion analysis method and on the velocity of human body skeleton key points change as well as the ratio change of body bounding box's width and height. The public data set was used to extract human skeletal features and to train deep learning, GRU, and as a result of an experiment to find a feature extraction method that can achieve high classification accuracy, the proposed method showed a 99.8% success rate in detecting falls more effectively than the conventional primitive skeletal data use method.

• Journal of the Korean Society of Costume
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• v.42
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• pp.69-90
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• 1999

Mannerism style evolved from the Renaissance style adopting the concept of grace as the ideal beauty, Having its ground on Neoplatonism the main goal of mannerism art was the realization of the invisible beauty over reality. Mannerism style in dress flourished in the sixteenth century court society, when courtly manners and courtly grace became the most important qualities in social relationship. Courtiers thought that courtly grace the ideal of beauty could be realized in the cultured and studied elegance. Mannerism style in dress evolved from the process of transforming and manipulating the Renaissance look for the abstract of beauty. The clothes of Mannerism style were against the natural movement of the human body. There was a tendency of refining and polishing the whole clothing and various technical skills were experim-ented on the mannerism style. The outstanding elements of this tendency can be found in the details like ruffs fathingale padding slashing puffing and etc. Mannerism intended to reconstruct the human body artificially to express courtly grace and novelty. During that process the new pose 'figura serpentinata' which is bizarre convoluted pose with full of flexibility was created. The expression of human body became more slender with elongated legs a torso with a long neck and a tiny head. This tendency of distorting the natural body forms were reflected in the formal characteristics of Mannerism dress style which is geometrical abstr-action unnatural elongation complex disposition and control with perfect ease.

• Journal of Advanced Navigation Technology
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• v.16 no.3
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• pp.545-552
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• 2012

In this paper, we propose Modified Multi CAMShift Algorithm based on Kalman filter and Weighted Search Windows(KWMCAMShift) that extracts skin color area and tracks several human body parts for real-time human tracking system. We propose modified CAMShift algorithm that generates background model, extracts skin area of hands and head, and tracks the body parts. Kalman filter stabilizes tracking search window of skin area due to changing skin area in consecutive frames. Each occlusion areas is avoided by using weighted window of non-search areas and main-search area. And shadows are eliminated from background model and intensity of shadow. The proposed KWMCAMShift algorithm can estimate human pose in real-time and achieves 96.82% accuracy even in the case of occlusions.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.5
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• pp.417-428
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• 2017

In this paper, we describe the architectural design, unit component hardware design and core software design(Helmet Pose Tracking Software and Terrain Elevation Data Correction Software) of IHDS(Intelligent Helmet Display System), and describe the results of unit test and integration test. According to the trend of the latest helmet display system, the specifications which includes 3D map display, FLIR(Forward Looking Infra-Red) display, hybrid helmet pose tracking, visor reflection type of binocular optical system, NVC(Night Vision Camera) display, lightweight composite helmet shell were applied to the design. Especially, we proposed unique design concepts such as the automatic correction of altitude error of 3D map data, high precision image registration, multi-color lighting optical system, transmissive image emitting surface using diffraction optical element, tracking camera minimizing latency time of helmet pose estimation and air pockets for helmet fixation on head. After completing the prototype of all system components, unit tests and system integration tests were performed to verify the functions and performance.

• Journal of KIISE:Software and Applications
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• v.35 no.10
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• pp.600-607
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• 2008

This paper proposes a robust human detection method irrespective of their pose variation using the multiple oriented 2D elliptical filters (MO2DEFs). The MO2DEFs can detect the humans regardless of their poses unlike existing object oriented scale adaptive filter (OOSAF). To overcome OOSAF's limitation, we introduce the MO2DEFs whose shapes look like the oriented ellipses. We perform human detection by applying four different 2D elliptical filters with specific orientations to the 2D spatial-depth histogram and then by taking the thresholds over the filtered histograms. In addition, we determine the human pose by using convolution results which are computed by using the MO2DEFs. We verify the human candidates by either detecting the face or matching head-shoulder shapes over the estimated rotation. The experimental results showed that the accuracy of pose angle estimation was about 88%, the human detection using the MO2DEFs outperformed that of using the OOSAF by $15{\sim}20%$ especially in case of the posed human.