• Journal of Advanced Navigation Technology
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• v.21 no.2
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• pp.200-205
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• 2017

Modern sports are developing into sports science that incorporates science and various analytical simulation systems for improving records are being developed, and they are helping to improve actual game records. Therefore golf which is one of various sports events, has been popularized among the hobbyists and the general public and there is an increasing demand for correcting the movement attitude of the person. In response to these demands, many systems have been developed to analyze and correct golf swing postures. The golf swing accuracy analysis system analyzes the moments that can not be seen with the naked eye and guides them to understand easily. It can improve the golf swing motion through immediate feedback due to the visual effect. Using the knowledge of golf swing motion collected from golf swing video, we improved reliability. In addition, it provides the ability to visually check and analyze your golf swing video, allowing you to analyze each segment based on various golf swing classification methods.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.659-662
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• 2008

In sports videos, text provides valuable information about the game such as scores and information about the players. This paper proposed a robust recognition method of player name in golf videos. In golf, most of users want to search the scenes which contain the play shots of favorite players. We use text information in golf videos for robust extraction of player information, By using OCR, we have obtained the text information, and then recognized the player information from player name DB. We can search the scenes of favorite players by using this player information. By conducting experiments on several golf videos, we demonstrate that our method achieves impressive performance with respect to the robustness.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.2
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• pp.180-187
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• 2010

In this paper, a GNSS-based AGV system was designed, and steering tested on a golf cart using electric wires in order to confirm the control efficiency of the low speed vehicle which used only position information of GNSS. After analyzed the existing AGVs system, we developed controller and steering algorithm using GNSS based position information. To analyze the performance of the developed controller and steering algorithm, straight-type and circle-type trajectory test are executed. The results show that steering performance of GNSS-based AGV system is ${\pm}\;0.2m$ for a reference trajectory.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.6
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• pp.74-80
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• 2009

Path tracking of unmanned vehicle is a basis of autonomous driving and navigation. For the path tracking, it is very important to find the exact position of a vehicle. GPS is used to get the position of vehicle and a direction sensor and a velocity sensor is used to compensate the position error of GPS. To detect path lines in a road image, the bird's eye view transform is employed, which makes it easy to design a lateral control algorithm simply than from the perspective view of image. Because the driving speed of vehicle should be decreased at a curved lane and crossroads, so we suggest the speed control algorithm used GPS and image data. The control algorithm is simulated and experimented from the basis of expert driver's knowledge data. In the experiments, the results show that bird's eye view transform are good for the steering control and a speed control algorithm also shows a stability in real driving.