• Journal of Institute of Control, Robotics and Systems
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• v.12 no.7
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• pp.700-705
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• 2006

This paper proposes a collision avoidance algorithm for two mobile robots with independent goals in a same workspace. Using skeleton map, an environment is presented as a graph consisting of nodes and arcs. Robots generate the shortest set of paths using the combination of objective functions of the two robots. Path for collision avoidance of a robot can be selected among three class; the shortest path, detour, paths with a waiting time at safety points around crossing points. Simulation results are presented to verify the efficiency of the proposed algorithms.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.1101-1104
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• 2019

키넥트는 RGBD 카메라로 인체의 뼈대와 관절을 3D 공간에서 스켈레톤 데이터수집을 가능하게 해주었다. 스켈레톤 데이터를 활용한 행동 분류는 RNN, CNN 등 다양한 인공 신경망으로 접근하고 있다. 본 연구는 키넥트를 이용해서 Skeleton Joints를 수집하고, DNN 기반 스켈레톤 모델링 학습으로 행동을 분류한다. Skeleton Joints Processing 과정은 키넥트의 Depth Map 기반의 Skeleton Tracker로 25가지 Skeleton Joints 좌표를 얻고, 학습을 위한 전처리 과정으로 각 좌표를 상대좌표로 변경하고 데이터 수를 제한하며, Joint가 트래킹 되지 않은 부분에 대한 예외 처리를 수행한다. 스켈레톤 모델링 학습 과정에선 3계층의 DNN 신경망을 구축하고, softmax_cross_entropy 함수로 Skeleton Joints를 집는 모션, 내려놓는 모션, 팔짱 낀 모션, 얼굴을 가까이 가져가는 모션 해서 4가지 행동으로 분류한다.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2790-2792
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• 2005

This paper proposes a path-planning algorithm that enables a robot to reach the goal position while avoiding obstacles. The proposed method, which is based on dynamic programming, finds an optimum path to follow using a modified skeleton map method which exploits information on obstacle positions. Simulation results show the feasibility of the proposed method.

• Journal of IKEEE
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• v.16 no.4
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• pp.369-374
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• 2012

This paper handles the UX implementation for system control using the visual input information of hand motion. Kinect sensor from Microsoft is used to acquire the user's skeleton image from the 3-D depth map at a rate of 30 frames per sec. and eventually knows the x-y coordinates of hand joints. The x-y coordinate value changes of hands between the present frame and next frame shows the direction of changes and rotation of changes and the various hand motion is used as a UX input command for remote image control on smart TV, etc. Through the experiments, we showed the implementation of the proposed idea.

• 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.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.97-108
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• 2022

The video-assisted human action recognition [1] field is one of the most active ones in computer vision research. Since the depth data [2] obtained by Kinect cameras has more benefits than traditional RGB data, research on human action detection has recently increased because of the Kinect camera. We conducted a systematic study of strategies for recognizing human activity based on deep data in this article. All methods are grouped into deep map tactics and skeleton tactics. A comparison of some of the more traditional strategies is also covered. We then examined the specifics of different depth behavior databases and provided a straightforward distinction between them. We address the advantages and disadvantages of depth and skeleton-based techniques in this discussion.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2575-2586
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• 2000

In this paper, we propose an algorithm which can automatically extract the road information in a map image. The proposed method extracts the road image in the complex map image. The extracted image is converted into the skeleton image by thining method. The converted image contains various problems. In order to correct these problems, after the road is classified by the number of Rutovitz-connectivity which represents the characteristic of road, those are respectively corrected according to the load characteristic. In the simulation, the proposed method has obtained good results for the various type of map images.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2004.11a
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• pp.301-306
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• 2004

The purpose of this study is to supply basic data for distinction of Support and Infill in Open Housing. This study is based on archive survey and actual investigation through visiting four sites in Japan, which are experimental SI(skeleton & infill) housings. We found a lot of distinction techniques and methods applied to the SI housings, and findings are applicable to the planning and designing works of apartment housings. Based on the theoretical Studies concerning the distinction and separation of SI housing, this study made out interface map for separation and distinction of housing components and examined a design method of separation accordingly.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.1
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• pp.81-88
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• 2002

This paper proposes an extraction method which extracts two different thematic maps, which have different line thickness from each other in a raster image that contains the two thematic maps. In the proposed method, the depth of each pixel is calculated according to the amount of pixels in its surrounding neighborhood, and then the thinning is performed. By using depth threshold, two thematic maps are first extracted from the thinning result. There are noise images and skeleton disconnection in the lines of each extracted thematic map. Each thematic map extraction is finally completed after removing the noise images and connecting the disconnected lines. Through the experiment, we showed that the proposed method could be used for the extraction of each thematic map of a raster image which included two thematic maps.

• Current Optics and Photonics
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• v.3 no.1
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• pp.54-65
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• 2019

To develop a biomarker predicting tumor treatment efficacy is helpful to reduce time, medical expenditure, and efforts in oncology therapy. In clinics, microvessel density using immunohistochemistry has been proposed as an indicator that correlates with both tumor size and metastasis of cancer. In the preclinical study, we hypothesized that vascular morphometrics using optical coherence tomography angiography (OCTA) could be potential indicators to estimate the treatment efficacy of breast cancer. To verify this hypothesis, a 13762-MAT-B-III rat breast tumor was grown in a dorsal skinfold window chamber which was applied to a nude mouse, and the change in vascular morphology was longitudinally monitored during tumor growth and metronomic cyclophosphamide treatment. Based on the daily OCTA maximum intensity projection map, multiple vessel parameters (vessel skeleton density, vessel diameter index, fractal dimension, and lacunarity) were compared with the tumor size in no tumor, treated tumor, and untreated tumor cases. Although each case has only one animal, we found that the vessel skeleton density (VSD), vessel diameter index and fractal dimension (FD) tended to be positively correlated with tumor size while lacunarity showed a partially negative correlation. Moreover, we observed that the changes in the VSD and FD are prior to the morphological change of the tumor. This feasibility study would be helpful in evaluating the tumor vascular response to treatment in preclinical settings.