• Proceedings of the Korean Society for Language and Information Conference
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• 1998.02a
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• pp.152-162
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• 1998

• TTA Journal
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• s.177
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• pp.103-106
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• 2018

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.34 no.9
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• pp.47-51
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• 2016

• KSCI Review
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• v.24 no.2
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• pp.1-5
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• 2016

• Journal of Korea Fair Competition Federation
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• no.109
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• pp.88-96
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• 2004

• Proceedings of the Optical Society of Korea Conference
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• 1996.09a
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• pp.81-81
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• 1996

• 대한방사선치료학회:학술대회논문집
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• 2000.04a
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• pp.9-9
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• 2000

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2001.06a
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• pp.69-86
• /
• 2001

• The Transactions of The Korean Institute of Electrical Engineers
• /
• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.1
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• pp.1-11
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• 2013

The determination of the pose of the imaging camera is a fundamental problem in computer vision. In the monocular case, difficulties in determining the scene scale and the limitation to bearing-only measurements increase the difficulty in estimating camera pose accurately. Many mobile phones now contain inertial measurement devices, which may lend some aid to the task of determining camera pose. In this study, by means of simulation and real-world experimentation, we explore an approach to monocular camera localization that incorporates both observations of the environment and measurements from accelerometers and gyroscopes. The unscented Kalman filter was implemented for this task. Our main contribution is a novel approach to landmark initialization in a Kalman filter; we characterize the tolerance to noise that this approach allows.