• Journal of Korea Multimedia Society
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• v.15 no.4
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• pp.501-507
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• 2012

Human body motion is a non-verbal part for interaction or movement that can be used to involves real world and virtual world. In this paper, we explain a study on natural user interface (NUI) in human hand motion recognition using RGB color information and depth information by Kinect camera from Microsoft Corporation. To achieve the goal, hand tracking and gesture recognition have no major dependencies of the work environment, lighting or users' skin color, libraries of particular use for natural interaction and Kinect device, which serves to provide RGB images of the environment and the depth map of the scene were used. An improved Camshift tracking algorithm is used to tracking hand motion, the experimental results show out it has better performance than Camshift algorithm, and it has higher stability and accuracy as well.

• Advances in robotics research
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• v.1 no.2
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• pp.127-140
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• 2014

This work presents an IR-based system for parking assistance and obstacle detection in the automotive field that employs the Microsoft Kinect camera for fast 3D point cloud reconstruction. In contrast to previous research that attempts to explicitly identify obstacles, the proposed system aims to detect "reachable regions" of the environment, i.e., those regions where the vehicle can drive to from its current position. A user-friendly 2D traversability grid of cells is generated and used as a visual aid for parking assistance. Given a raw 3D point cloud, first each point is mapped into individual cells, then, the elevation information is used within a graph-based algorithm to label a given cell as traversable or non-traversable. Following this rationale, positive and negative obstacles, as well as unknown regions can be implicitly detected. Additionally, no flat-world assumption is required. Experimental results, obtained from the system in typical parking scenarios, are presented showing its effectiveness for scene interpretation and detection of several types of obstacle.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.07a
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• pp.375-378
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• 2013

인터넷 통신량의 대부분이 주문형 비디오(VOD) 서비스임은 이미 널리 알려진 바와 같다. VOD 사용자 인터페이스가 사용자의 손동작을 인식한다면 노인, 유아, 장애인 등 리모트컨트롤의 사용이 쉽지 않은 사용자들도 편리하게 VOD를 즐길 것이다. 게임 등에서는 이미 키넥트(KINECT)를 이용한 사용자 인터페이스가 널리 사용되고 있어, 본 논문은 키넥트를 이용한 VOD 사용자 인터페이스를 제안한다. 제안한 사용자 인터페이스는 키넥트에서 얻을 수 있는 손의 좌표와 깊이 정보 데이터를 이용하여, 사용자가 메뉴를 선택하는 것을 인식하고 사용자가 비디오를 선택하면 해당 동영상 콘텐츠를 재생하는 등의 적절한 동작을 한다. 동영상 콘텐츠는 네트워크 상에서 멀티미디어 데이터 스트리밍 방법에 대한 표준안인 RTSP(Real-time Streaming Protocol)로 전송하여 실시간으로 동영상을 재생한다.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.1
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• pp.40-45
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• 2015

In this paper, we present an algorithm for the analysis of poses while playing table-tennis using action recognition. We use Kinect as the 3D sensor and 3D skeleton data provided by Kinect for further processing. We adopt a spherical coordinate system and feature selected using k-means clustering. We automatically detect the starting and ending frame and discriminate the action of table-tennis into two groups of forehand and backhand swing. Each swing is modeled using HMM(Hidden Markov Model) and we used a dataset composed of 200 sequences from two players. We can discriminate two types of table tennis swing in real-time. Also, it can provide analysis according to similarities found in good poses.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.11a
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• pp.346-348
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• 2011

IT 산업이 발달함에 따라 무인화 시스템 역시 발달하고 있다. 또한 인간의 수명이 늘어나면서 삶의 질을 보다 높이기 위한 활동을 중요시 여기고 있다. 따라서 일반인뿐만이 아닌 노인이나 장애인도 주변의 도움 없이 운동을 가능케 하여 삶의 질을 높일 수 있는 프로그램 연구가 활발히 진행되고 있다. 이 두 가지에 초점을 맞추어 본 논문에서는 Kinect를 이용하여 실시간으로 팔운동을 감지하는 방법을 제안한다. Kinect를 통해 사람을 구별해 낸 뒤 팔만을 감지하게 된다. Kinect를 통해 얻어지는 실시간 영상으로 팔이 움직이는 각도를 계산하기 위해 팔의 point를 찾아낸다. 팔이 구부러진 정도와 펴진 정도를 실시간으로 계산하여 사용자에게 보여주고, 횟수 또한 사용자가 별도의 count 작업을 하지 않더라도 화면에 보일 수 있도록 하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.4
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• pp.249-255
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• 2014

We present a simple method to watermark three-dimensional (3D) triangular meshes that have been generated from the depth data of the Kinect sensor. In contrast to previous methods, which maintain the shape of 3D triangular meshes and decide the embedding place, requiring calculations of vertices and their neighbors, our method is based on selecting one of the coordinate axes. To maintain shape, we use discrete wavelet transform and constant regularization. We know that the watermarking system needs the information to be embedded; we used a text to provide that information. We used geometry attacks such as rotation, scales, and translation, to test the performance of this watermarking system. Performance parameters in this paper include the vertices error rate (VER) and bit error rate (BER). The results from the VER and BER indicate that using a correction term before the extraction process makes our system robust to geometry attacks.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.10
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• pp.921-927
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• 2013

This paper presents a user interface for vision based indirect teaching of a robotic manipulator with Kinect and IMU (Inertial Measurement Unit) sensors. The user interface system is designed to control the manipulator more easily in joint space, Cartesian space and tool frame. We use the skeleton data of the user from Kinect and Wrist-mounted IMU sensors to calculate the user's joint angles and wrist movement for robot control. The interface system proposed in this paper allows the user to teach the manipulator without a pre-programming process. This will improve the teaching time of the robot and eventually enable increased productivity. Simulation and experimental results are presented to verify the performance of the robot control and interface system.

• Journal of Computational Design and Engineering
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• v.2 no.2
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• pp.73-78
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• 2015

In this paper, we propose a new approach to providing interactive and collaborative lens among multi-users for supporting level-of-detailed views using smartphones in a public display. In order to provide smartphone-based lens capability, the locations of smartphones are effectively detected and tracked using Kinect, which provides RGB data and depth data (RGB-D). In particular, human skeleton information is extracted from the Kinect 3D depth data to calculate the smartphone location more efficiently and correctly with respect to the public display and to support head tracking for easy target selection and adaptive view generation. The suggested interactive and collaborative lens using smartphones not only can explore local spaces of the shared display but also can provide various kinds of activities such as LOD viewing and collaborative interaction. Implementation results are given to show the advantage and effectiveness of the proposed approach.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.155-156
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• 2014

본 논문에서는 키넥트 기반의 동물농장 게임을 설계하고 구현한다. 이 게임은 다양한 동물과 울음소리를 이용하여 유아의 지능 및 신체 발달을 목적으로 하는 유아 교육용 게임이다. 다양한 동물 이미지는 랜덤하게 화면에 출력되고, 플레이어는 화면에 출력된 동물 이미지를 순서대로 터치함으로써 점수를 획득하도록 구현한다. 또한 화면에 출력된 동물 이미지를 터치하면 해당 동물의 울음소리를 출력하도록 구현한다. 플레이어의 동작은 키넥트를 이용하여 인지한 플레이어의 스켈리톤 정보를 전송 받아 이용한다.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.11
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• pp.1003-1007
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• 2015

Depth calibration is a procedure for finding the conversion function that maps disparity data from a depth-sensing camera to actual distance information. In this paper, we present an optimal depth calibration method for Kinect$^{TM}$ sensors based on an experimental design and convex optimization. The proposed method, which utilizes multiple measurements from only two points, suggests a simplified calibration procedure. The confidence ellipsoids obtained from a series of simulations confirm that a simpler procedure produces a more reliable calibration function.