• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.6
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• pp.1237-1242
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• 2017

Computer vision is coming more interesting with new imaging sensors' new capabilities which enable it to understand more its surrounding environment by imitating human vision system with artificial intelligence techniques. In this paper, we made experiments with Kinect camera, a new depth sensor for object detection and distance measurement functions, most essential functions in computer vision such as for unmanned or manned vehicles, robots, drones, etc. Therefore, Kinect camera is used here to estimate the position or the location of objects in its field of view and measure the distance from them to its depth sensor in an accuracy way by checking whether that the detected object is real object or not to reduce processing time ignoring pixels which are not part of real object. Tests showed promising results with such low-cost range sensor, Kinect camera which can be used for object detection and distance measurement which are fundamental functions in computer vision applications for further processing.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.07a
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• pp.33-34
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• 2014

본 논문에서는 Kinect 기반의 모니터 제어 기법을 설계하고 구현한다. 이 기법은 Kinect의 Joint 기능을 활용하여 신체의 구조를 인식하고 손과 머리의 Joint를 받아온다. Kinect의 카메라는 손 동작을 추적하여 Joint 신체 부위에 해당하는 Joint 값을 모니터의 좌표 값으로 변환함으로써 손 동작에 따라 마우스를 움직이는 기능을 구현한다. 그리고 파워포인트에서 사용하는 F5, Esc, Right, Left 키에 대하여 Joint의 좌표 값이 일정 범위를 초과하면 마우스 클릭 이벤트를 발생하도록 구현함으로써 파워포인트의 슬라이드 화면을 제어하는 기능을 구현한다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.439-446
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• 2017

Portable low-cost Kinect sensor was used to analyze standing balance ability of the elderly. Eighty subjects who can walk alone and have a normal cognitive level participated in this experiment. Based on Berg Balance scale (BBS) test with 52 points, subjects were divided into Healthy older (HO: 46 persons, BBS: $53.80{\pm}1.19$) and Impaired older (IO: 34 persons, BBS: $49.06{\pm}2.03$) group. Each subject performed 30 seconds four different standing balance tests (EO: Eyes Open, EC: Eyes Close, EOf: Eyes Open on foam, ECf: Eyes Close on foam). Five variables (Mean distance, Range of distance, Root mean square, Mean velocity, 95% ellipse area) were calculated from the hip joint center movement of Kinect sensor. Results showed that there were significant differences between groups for four different standing tests. Calculated variables from kinect sensor showed significant correlation with BBS score. Especially, mediolateral mean distance, mediolateral root mean square, mediolateral range of distance and 95% ellipse area showed discriminative ability for all tests. Mean values of variables of IO were higher than those of HO, which means the decreased balance ability in IO compared with HO. Therefore, it was possible to estimate simple balance assessment of the elderly using portable low-cost Kinect sensor.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.611-613
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• 2015

Multimedia classroom teaching as well as the automatic tracking of the camera are automatically saved track to be saved. The existing tracking system is attached to the body by a separate sensor to track or on the front of the sensor to the construction of the track was a hit at the same time in front of the discomfort caused by tracking errors when I had an issue that shouldn't be. In this paper, Microsoft-Kinect sensor, using the speaker's position and behavior analysis (instructor), and PTZ cameras, recording systems, storage classes and lectures with classroom lessons can be effective at the time of recording to the content production about the technology of unmanned speaker tracking solution.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.9
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• pp.957-963
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• 2014

This paper proposes a predictive control for an efficient human following robot using Kinect sensor. Especially, this research is focused on detecting of foot-end-point and foot-vector instead of human body which can be occluded easily by the obstacles. Recognition of the foot-end-point by the Kinect sensor is reliable since the two feet images can be utilized, which increases the detection possibility of the human motion. Depth image features and a decision tree have been utilized to estimate the foot end-point precisely. A tracking point average algorithm is also adopted in this research to estimate the location of foot accurately. Using the continuous locations of foot, the human motion trajectory is estimated to guide the mobile robot along a smooth path to the human. It is verified through the experiments that detecting foot-end-point is more reliable and efficient than detecting the human body. Finally, the tracking performance of the mobile robot is demonstrated with a human motion along an 'L' shape course.

• Journal of Sensor Science and Technology
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• v.24 no.1
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• pp.69-77
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• 2015

The Microsoft Kinect is a motion sensing input device which is widely used for many motion recognition applications such as fitness, sports, and rehabilitation. Until now, most of remote rehabilitation systems with the Microsoft Kinect have allowed the user or patient to do rehabilitation or fitness by following the motion of a video screen. However in this paper we propose a smart remote rehabilitation system with the Microsoft Kinect motion sensor and a wearable ECG sensor which can allow patients to offer monitoring of the individual's performance and personalized feedback on rehabilitation exercises. The proposed noble smart remote rehabilitation is able to monitor and measure the state of the patient's condition during rehabilitation exercise, and transmits it to the prescriber. This system can give feedback to a prescriber, a doctor and a patient for improving and recovering motor performance. Thus, the efficient rehabilitation training service can be provided to patient in response to changes of patient's condition during exercise.

• The Journal of Korea Robotics Society
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• v.10 no.1
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• pp.16-23
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• 2015

This paper presents a method of improving the pose recognition accuracy of objects by using Kinect sensor. First, by using the SURF algorithm, which is one of the most widely used local features point algorithms, we modify inner parameters of the algorithm for efficient object recognition. The proposed method is adjusting the distance between the box filter, modifying Hessian matrix, and eliminating improper key points. In the second, the object orientation is estimated based on the homography. Finally the novel approach of Auto-scaling method is proposed to improve accuracy of object pose estimation. The proposed algorithm is experimentally tested with objects in the plane and its effectiveness is validated.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.01a
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• pp.53-54
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• 2013

본 논문에서는 Kinect에서 제공하는 조인트와 스캘리톤 정보를 활용하여 Windows Phone 7 게임을 설계하고 구현한다. 이 게임은 Kinect를 사용하여 조인트의 x, y, z 좌표값 정보를 활용하면 Windows 화면의 depth 영상에 골격들을 표시할 수 있도록 구현한다. 또한 몸을 움직일 때 마다 각 관절 정보인 조인트를 추적하여 특정 포인트를 찾아내는 기능을 구현하여 인체의 움직임을 감지할 수 있도록 구현한다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.4
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• pp.565-569
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• 2014

Recently, various kinds of new computer controlled devices have been introduced in a wide range of areas, and convenient user interfaces for controlling the devices are strongly needed. To implement natural user interfaces(NUIs) on top of the devices, new technologies like a touch screen, Wii Remote, wearable interfaces, and Microsoft Kinect were presented. This paper presents a natural and intuitive gesture-based model for controlling contents of LCD display. Microsoft Kinect sensor and its SDK are used to recognize human gestures, and the gestures are interpreted into corresponding commands to be executed. A command dispatch model is also proposed in order to handle the commands more naturally. I expect the proposed interface can be used in various fields, including display contents control.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.49-50
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• 2016

본 논문에서는 Kinect 센서 기반의 카드 매칭 게임을 설계하고 구현한다. 이 게임은 유아용 카드 매칭 게임으로 카드 뒷면을 화면에 배치시키고 무작위로 앞면의 그림을 보여준다. 플레이어는 앞면의 그림을 위치별로 기억하여 같은 짝의 그림을 선택하여 맞춘다. 다른 짝을 매칭 할 경우 다시 뒷면으로 뒤집히고 같은 짝을 매칭 할 경우는 해당 그림의 영어 단어를 팝업시킨다. 예를 들어 토끼 그림의 짝을 매칭 할 경우 RABBIT이란 단어를 팝업 시킨다. 그리고 플레이어는 RABBIT이란 단어를 발음하면 Kinect는 음성을 인식하여 팝업된 창을 종료하고, 게임을 계속 진행한다. 게임은 화면에 배치시키는 카드를 $2{\times}2$부터 시작하여 난이도 별로 증가 시키고 스테이지 별로 콘텐츠를 나눠 영유아들이 재미있게 게임을 즐기면서 영어 단어를 학습할 수 있는 게임이다.