• Transactions of the KSME C: Technology and Education
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• v.1 no.2
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• pp.205-210
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• 2013

In this research, we have developed a ski-simulation system based on a physics-based simulation model using Newton's second law of motion. Key parameters of the model, which estimates skier's trajectory, speed and acceleration change due to skier's control on ski plate and posture changes, were derived from a field test study performed on real ski slope. Skier's posture and motion were measured by motion capture system composed of 13 high speed IR camera, and skier's control and pressure distribution on ski plate were measured by acceleration and pressure sensors attached on ski plate and ski boots. Developed ski-simulation model analyzes user's full body and center of mass using a depth camera(Microsoft Kinect) device in real time and provides feedback about force, velocity and acceleration for user. As a result, through the development of interactive ski-simulation motion recognition system, we accumulated experience and skills based on physics models for development of sports simulator.

• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.509-523
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• 2005

We are developing a novel framework, PRIDE (PRediction In Dynamic Environments), to perform moving object prediction (MOP) for autonomous ground vehicles. The underlying concept is based upon a multi-resolutional, hierarchical approach which incorporates multiple prediction algorithms into a single, unifying framework. The lower levels of the framework utilize estimation-theoretic short-term predictions while the upper levels utilize a probabilistic prediction approach based on situation recognition with an underlying cost model. The estimation-theoretic short-term prediction is via an extended Kalman filter-based algorithm using sensor data to predict the future location of moving objects with an associated confidence measure. The proposed estimation-theoretic approach does not incorporate a priori knowledge such as road networks and traffic signage and assumes uninfluenced constant trajectory and is thus suited for short-term prediction in both on-road and off-road driving. In this article, we analyze the complementary role played by vehicle kinematic models in such short-term prediction of moving objects. In particular, the importance of vehicle process models and their effect on predicting the positions and orientations of moving objects for autonomous ground vehicle navigation are examined. We present results using field data obtained from different autonomous ground vehicles operating in outdoor environments.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.6
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• pp.323-334
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• 2014

In this paper, we proposed indoor positioning system with improved accuracy. The proposed indoor location measurement system is based pedestrian location measurement method that use the embedded sensor of smartphone. So, we do not need wireless external resources, such as GPS or WiFi signals. The conventional methods measure indoor location by generating a movement route of pedestrian by step and direction recognition. In this paper, to correct the direction sensor error, we use the common feature of the normal indoor floor map that the indoor path is lattice-structured. And we quantize moving directions depending on the direction of indoor path. In addition, we propose moving direction measuring method using geomagnetic sensor and gyro sensor to improve the accuracy. Also, the proposed step detection method uses angle and accelerometer sensors. The proposed step detection method is not affected by the posture of the smartphone. Direction errors caused by direction sensor error is corrected due to proposed moving direction measuring method. The proposed location error correction method corrects location error caused by step detection error without the need for external wireless signal resources.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2016.05a
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• pp.285-286
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• 2016

We aim to propose the prediction modeling method of ship's position with extracting ship's trajectory model through pattern recognition based on the data that are being collected in VTS centers at real time. Support Vector Machine algorithm was used for data modeling. The optimal parameters are calculated with k-fold cross validation and grid search. We expect that the proposed modeling method could support VTS operators' decision making in case of complex encountering traffic situations.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.11a
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• pp.202-202
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• 2008

The world gross market of many kinds of electronics, such as TV and mobile phone has been increasing rapidly these days. It is mainly caused by the amazing developments of IT technology during past decade and the changes of individual life style for the better. Thanks to the increases of electronics manufactured in quantity, much more electronic components such as MLCC (multi layer ceramic capacitor) and PCB (printed circuit board), which are our main products, have been needed as a consequence. Though it was reported that total market of electronic components exceeds several hundreds of billion dollars, there are many manufactures struggling for survival in the competition of electronics components. Then the recognition of quality as a key technology has spread and the efforts for high-yield production lines have been kept in many companies. In this paper, our efforts to eliminate the contamination of particles and the diffusion of some volatile organic compounds which is very harmful to workers at production line have been introduced.

• 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 the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1217-1227
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• 2017

Deep learning has been studied explosively and has achieved excellent performance in areas like image and speech recognition, the application areas in which computations have been challenges with ordinary machine learning techniques. The theoretical study of deep learning has also been researched toward improving the performance. In this paper, we try to find a key of the success of the deep learning in rich and efficient expressiveness of the deep learning function, and analyze the theoretical studies related to it.

• The Journal of the Acoustical Society of Korea
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• v.21 no.7
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• pp.641-647
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• 2002

In this paper, we propose the reduction method of the number of parameters in the segmental-feature HMM using trend quantization method. The proposed method shares the trend information of the polynomial trajectories by quantization. The trajectory is obtained by the sequence of feature vectors of speech signals and can be divided by trend and location information. The trend indicates the variation of consequent frame features, while the location points to the positional difference of the trajectories. Since the trend occupies the large portion of SFHMM, if the trend is shared, the number of parameters maybe decreases. To exploit the proposed system the experiments are performed on TIMIT corpus. The experimental results show that the performance of the proposed system is roughly similar to that of previous system. Therefore, the proposed system can be considered one of parameter reduction method.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.1
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• pp.19-26
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• 2004

In this paper, we suggest a 3D vision inspection method which use only one camera. If we have the database of pattern and can recognize the object, and also estimate the rotated shape of the parts, we can inspect the parts using only one image. We used the 3D database and the 2D geometrical pattern matching, and the rotation transition theory about the algorithm. As the results, we could have the capability of the recognition and inspection of the rotated object through the estimation of rotation an81e. We applied our suggested algorithm to the inspection of typical IC and capacitor, and compared our suggested algorithm with the conventional 2D inspection method and the feature space trajectory method.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1225-1235
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• 2016

This paper presents a method for computer-assisted slide presentation using vision-based gesture recognition. The proposed method consists of a sequence of steps, first detecting a hand in the scene of projector beam, then estimating the smooth trajectory of a hand or a pointing finger using Kalman Filter, and finally interfacing to an application system. Additional slide navigation control includes moving back and forth the pages of the presentation. The proposed method is to help speakers for an effective presentation with natural improved interaction with the computer. In particular, the proposed method of using finger pointing is believed to be more effective than using a laser pointer since the hand, the pointing or finger are more visible and thus can better grab the attention of the audience.