• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.197-207
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• 2014

In this paper, I propose an automatic extraction method of golf swing features using a practical TOF camera Kinect. I extracted 7 key swing frames and features using joints and depth information from a Kinect. I tested the proposed method on 50 swings from 10 players and showed the performace. It is meaningful that 3D swing features are extracted automatically using an inexpensive and simple system and specific numerical feature values can be used for the building of automatic swing analysis system.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• fall
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• pp.268-269
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• 2021

본 논문에서는 RGB이미지와 Depth 이미지를 촬영할 수 있는 촬영 장비인 Azure Kinect를 사용해 다시점 촬영 시스템 구성을 위한 카메라 동기화 시스템을 제안한다. 제안한 시스템에는 8대의 Azure Kinect 카메라를 사용하고 있으며 각 카메라는 3.5-mm 오디오 케이블로 연결되어 외부동기화 신호를 전달한다. 그리고 이미지를 저장할 때 발생하는 메모리에서의 병목현상을 최소화하기 위해 촬영 시스템의 동작을 16개의 버퍼로 나누어 병렬 컴퓨팅으로 진행한다. 이후 동기화 여부에 따른 차리를 디바이스 타임스탬프를 기준으로 하여 비교한다.

• Journal of Biomedical Engineering Research
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• v.36 no.5
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• pp.228-234
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• 2015

The balance ability significantly decreased in the elderly because of deterioration of the neural musculature regulatory mechanisms. Several studies have investigated methods of improving balance ability using real-time systems, but it is limited by the expensive test equipment and specialized resources. Recently, Kinect system based on depth data has been applied to address these limitations. Little information about accuracy/inaccuracy of Kinect system is, however, available, particular in motion analysis for evaluation of effectiveness in rehabilitation training. Therefore, the aim of the current study was to evaluate accuracy/inaccuracy of Kinect system in specific rotational movement for balance rehabilitation training. Six healthy male adults with no musculoskeletal disorder were selected to participate in the experiment. Movements of the participants were induced by controlling the base plane of the balance training equipment in directions of AP (anterior-posterior), ML (medial-lateral), right and left diagonal direction. The dynamic motions of the subjects were measured using two Kinect depth sensor systems and a three-dimensional motion capture system with eight infrared cameras for comparative evaluation. The results of the error rate for hip and knee joint alteration of Kinect system comparison with infrared camera based motion capture system occurred smaller values in the ML direction (Hip joint: 10.9~57.3%, Knee joint: 26.0~74.8%). Therefore, the accuracy of Kinect system for measuring balance rehabilitation traning could improve by using adapted algorithm which is based on hip joint movement in medial-lateral direction.

• Aerospace Engineering and Technology
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• v.11 no.2
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• pp.140-148
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• 2012

For autonomous navigation, map, pose tracking, and finding the shortest path are required. Because there is no GPS signal in indoor environment, the current position should be recognized in the 3D map by using image processing or something. In this paper, we explain 3D map creation technology by using depth camera like Kinect and pose tracking in 3D map by using 2D image taking from camera. In addition, the mechanism of avoiding obstacles is discussed.

• The Journal of Korea Robotics Society
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• v.9 no.2
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• pp.96-103
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• 2014

Global localization is one of the essential issues for mobile robot navigation. In this study, an indoor global localization method is proposed which uses a Kinect sensor and a monocular upward-looking camera. The proposed method generates an environment map which consists of a grid map, a ceiling feature map from the upward-looking camera, and a spatial feature map obtained from the Kinect sensor. The method selects robot pose candidates using the spatial feature map and updates sample poses by particle filter based on the grid map. Localization success is determined by calculating the matching error from the ceiling feature map. In various experiments, the proposed method achieved a position accuracy of 0.12m and a position update speed of 10.4s, which is robust enough for real-world applications.

• Journal of Broadcast Engineering
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• v.18 no.3
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• pp.393-400
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• 2013

Hand shape recognition is a fundamental technique for implementing natural human-computer interaction. In this paper, we discuss a method for effectively detecting a hand region in Kinect-based hand shape recognition. Since Kinect is a camera that can capture color images and infrared images (or depth images) together, both images can be exploited for the process of detecting a hand region. That is, a hand region can be detected by finding pixels having skin colors or by finding pixels having a specific depth. Therefore, after analyzing the performance of each, we need a method of properly combining both to clearly extract the silhouette of hand region. This is because the hand shape recognition rate depends on the fineness of detected silhouette. Finally, through comparison of hand shape recognition rates resulted from different hand region detection methods in general environments, we propose a high-performance hand region detection method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.248-251
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• 2016

This thesis has discussed how to recognize and convert raised letters on tire to data and collect such data. Unlike the existing recognition system, the system presented by this thesis recognizes raised letters on tire through detecting letters after converting the Kinect camera image into image data in the preprocessing stage. After then, numbers and letters are analyzed through image improvement by use of binary images, noise filter, etc. In the recognition stage, letter distinction is used and raised letters on tire are recognized 100% through correction of errors by way of the correction algorithm for tire data recognition errors. In this paper it will be the development of a method of recognizing characters and the tire technology. Although there are many ways to the already recognized characters, Tire characters requires a technique different from the more general character recognition. For this reason and to develop additional technical methods and algorithms for character recognition.

• 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.

• 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.