• Korean Journal of Applied Biomechanics
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• v.13 no.3
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• pp.81-98
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• 2003

The purpose of this study is to closely examine kinematic characteristics by jump phase of Li Xiaopeng motion in horse vaulting and provide the training data. In doing so, as a result of analyzing kinematic variables through 3-dimensional cinematographic using the high-speed video camera to Li Xiaopeng motion first performed at the men's vault competition at the 14th Busan Asian Games, the following conclusion was obtained. 1. It was indicated that at the post-flight, the increase of flight time and height and twisting rotational velocity has a decisive effect on the increase of twist displacement. And Li Xiaopeng motion showed longer flight time and higher flight height than Ropez motion with the same twist displacement of entire movement. Also the rotational displacement of the trunk at peak of COG was much short of $360^{\circ}$(one rotation) but twist displacement showed $606^{\circ}$. Likewise, Li Xiaopeng motion was indicated to concentrate on twist movement in the early flight. 2. It was indicated that at the landing, Li Xiaopeng motion gets the hip to move back, the trunk to stand up and the horizontal velocity of COG to slow down. This is thought to be the performance of sufficient landing, resulting from large security of rotational displacement of airborne and twist displacement. 3. It was indicated that at the board contact, Li Xiaopeng motion made a rapid rotation uprighting the trunk to recover slowing velocity caused by jumping with the horse in the back, and has already twisted the trunk nearly close to $40^{\circ}$ at board contact. Under the premise that elasticity is generated without the change of the feet contacting the board, it will give an aid to the rotation and twist of pre-flight. Thus, in the round-oH phase, the tap of waist according to the fraction and extension of hip joint and arm push is thought to be very important. 4. It was indicated that at the pre-flight, Li Xiaopeng motion showed bigger movement than the techniques of precedented studies rushing to the horse, and overcomes the concern of relatively low power of jump through the rapid rotation of the trunk. Li Xiaopeng motion secured much twist distance, increased rotational distance with the trunk bent forward, resulting in the effect of rushing to the horse. 5. At horse contact, Li Xiaopeng motion makes a short-time contact, and maintains horse take-off angle close to vertical, contributing to the increase of post-flight time and height. This is thought to be resulted from rapid move toward movement direction along with the rotational velocity of trunk rapidly earned prior to horse contact, and little shave of rotation axis according to twist motion because of effective twist in the same direction.

• The KIPS Transactions:PartB
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• v.17B no.5
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• pp.345-354
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• 2010

Visual tracking techniques for Augmented Reality are classified as either a marker tracking approach or a natural feature tracking approach. Marker-based tracking algorithms can be efficiently implemented sufficient to work in real-time on mobile devices. On the other hand, natural feature tracking methods require a lot of computationally expensive procedures. Most previous natural feature tracking methods include heavy feature extraction and pattern matching procedures for each of the input image frame. It is difficult to implement real-time augmented reality applications including the capability of natural feature tracking on low performance devices. The required computational time cost is also in proportion to the number of patterns to be matched. To speed up the natural feature tracking process, we propose a novel fast tracking method based on optical flow. We implemented the proposed method on mobile devices to run in real-time and be appropriately used with mobile augmented reality applications. Moreover, during tracking, we keep up the total number of feature points by inserting new feature points proportional to the number of vanished feature points. Experimental results showed that the proposed method reduces the computational cost and also stabilizes the camera pose estimation results.

• Journal of Biosystems Engineering
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• v.43 no.2
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• pp.148-159
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• 2018

Purpose: Unmanned air vehicle (UAV) remote sensing was applied to test various vegetation indices and make prediction models of protein content of rice for monitoring grain quality and proper management practice. Methods: Image acquisition was carried out by using NIR (Green, Red, NIR), RGB and RE (Blue, Green, Red-edge) camera mounted on UAV. Sampling was done synchronously at the geo-referenced points and GPS locations were recorded. Paddy samples were air-dried to 15% moisture content, and then dehulled and milled to 92% milling yield and measured the protein content by near-infrared spectroscopy. Results: Artificial neural network showed the better performance with $R^2$ (coefficient of determination) of 0.740, NSE (Nash-Sutcliffe model efficiency coefficient) of 0.733 and RMSE (root mean square error) of 0.187% considering all 54 samples than the models developed by PR (polynomial regression), SLR (simple linear regression), and PLSR (partial least square regression). PLSR calibration models showed almost similar result with PR as 0.663 ($R^2$) and 0.169% (RMSE) for cloud-free samples and 0.491 ($R^2$) and 0.217% (RMSE) for cloud-shadowed samples. However, the validation models performed poorly. This study revealed that there is a highly significant correlation between NDVI (normalized difference vegetation index) and protein content in rice. For the cloud-free samples, the SLR models showed $R^2=0.553$ and RMSE = 0.210%, and for cloud-shadowed samples showed 0.479 as $R^2$ and 0.225% as RMSE respectively. Conclusion: There is a significant correlation between spectral bands and grain protein content. Artificial neural networks have the strong advantages to fit the nonlinear problem when a sigmoid activation function is used in the hidden layer. Quantitatively, the neural network model obtained a higher precision result with a mean absolute relative error (MARE) of 2.18% and root mean square error (RMSE) of 0.187%.

• Journal of KIISE:Software and Applications
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• v.41 no.7
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• pp.481-491
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• 2014

The power production using renewable energy is more important because of a limited amount of fossil fuel and the problem of global warming. A concentrative photovoltaic system comes into the spotlight with high energy production, since the rate of power production using solar energy is proliferated. These systems, however, need to sophisticated tracking methods to give the high power production. In this paper, we propose a hierarchical tracking system using modular Bayesian networks and a naive Bayes classifier. The Bayesian networks can respond flexibly in uncertain situations and can be designed by domain knowledge even when the data are not enough. Bayesian network modules infer the weather states which are classified into nine classes. Then, naive Bayes classifier selects the most effective method considering inferred weather states and the system makes a decision using the rules. We collected real weather data for the experiments and the average accuracy of the proposed method is 93.9%. In addition, comparing the photovoltaic efficiency with the pinhole camera system results in improved performance of about 16.58%.

• The Journal of the Korea Contents Association
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• v.12 no.4
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• pp.143-155
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• 2012

The research was started out of curiosity for what made 's fast and trilling pace possible although it is an old movie. The center of what made it possible was its use of the Long Take - Long Take was used in all of the scenes and in some cases only long take was used. What is interesting is the film maker's use of various cinematic techniques to prevent the scene from being too slow and keep the audience immersed in the characters. In one shot, acting in addition to Mise-en-Sc$\grave{e}$ne were used to provide psychological immersion of character and scene. The use of Long Take, with the exception of some intentional scenes, was difficult to notice without conscience observation. All the components that make up Long Take. camera walking and lighting as well as actor's dialog and performance and scene movement all beautifully came together. The Long Take is generally replaced by many different sort shots. However, Mike Nichols clearly demonstrates the benefit of Long Take. In the movie, the general aesthetics from the use of Long Take is slightly altered for a different purpose. The specific methods and effects used in the application of Long Take is the subject of this study.

• The Journal of the Korea Contents Association
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• v.7 no.4
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• pp.1-9
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• 2007

Cellular operators develop high speed mobile internet and multi-function cellular phones to activate new business model based on mobile internet services. Domestic cellular operators evolve their mobile networks from cdma2000-1x and EvDo to HSDPA to activate high speed mobile internet services. They also develop mobile internet platforms such as WIPI, BREW, and J2ME on multi-function cellular phones having multimedia solutions such as camera, MP3, MPEG, 3D game engine, DMB, PAN such as bluetooth, IrDA, W-LAN, and location information using GPS. But, content providers have problems of redevelopment of the same mobile internet application on different mobile internet platforms provided by cellular operators. In this paper, we develop conversion solutions for interoperability of mobile internet applications on WIPI and BREW using an one-pass compiler. We confirm the performance the proposed conversion solutions for the API conversion rate, the converted file size, and the full conversion time using the popular mobile games which are the killer applications on WiPI and BREW.

• Journal of Korea Multimedia Society
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• v.15 no.10
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• pp.1196-1204
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• 2012

In this paper, a series of algorithms are proposed for controlling different kinds of multimedia contents and realizing interact between human and computer by using single input device. Human gesture recognition based on NUI is presented firstly in my paper. Since the image information we get it from camera is not sensitive for further processing, we transform it to YCbCr color space, and then morphological processing algorithm is used to delete unuseful noise. Boundary Energy and depth information is extracted for hand detection. After we receive the image of hand detection, PCA algorithm is used to recognize hand posture, difference image and moment method are used to detect hand centroid and extract trajectory of hand movement. 8 direction codes are defined for quantifying gesture trajectory, so the symbol value will be affirmed. Furthermore, HMM algorithm is used for hand gesture recognition based on the symbol value. According to series of methods we presented, we can control multimedia contents by using human gesture recognition. Through large numbers of experiments, the algorithms we presented have satisfying performance, hand detection rate is up to 94.25%, gesture recognition rate exceed 92.6%, hand posture recognition rate can achieve 85.86%, and face detection rate is up to 89.58%. According to these experiment results, we can control many kinds of multimedia contents on computer effectively, such as video player, MP3, e-book and so on.

• Journal of Korea Multimedia Society
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• v.16 no.6
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• pp.764-781
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• 2013

In this paper, we propose a highly precise vehicle detection method with low false alarm using billboard sweep stereo matching and multi-stage hypothesis generation. First, we capture stereo images from cameras established in front of the vehicle and obtain the disparity map in which the regions of ground plane or background are removed using billboard sweep stereo matching algorithm. And then, we perform the vehicle detection and tracking on the labeled disparity map. The vehicle detection and tracking consists of three steps. In the learning step, the SVM(support vector machine) classifier is obtained using the features extracted from the gabor filter. The second step is the vehicle detection which performs the sobel edge detection in the image of the left camera and extracts candidates of the vehicle using edge image and billboard sweep stereo disparity map. The final step is the vehicle tracking using template matching in the next frame. Removal process of the tracking regions improves the system performance in the candidate region of the vehicle on the succeeding frames.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.3
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• pp.177-186
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• 2012

In this paper, we propose a real-time approach for detecting and tracking a hand region by analyzing depth images. We build a hand model in advance. The model has the shape information of a hand. The detecting process extracts out moving areas in an image, which are possibly caused by moving a hand in front of a camera. The moving areas can be identified by analyzing accumulated difference images and applying the region growing technique. The extracted moving areas are compared against a hand model to get justified as a hand region. The tracking process keeps the track of center points of hand regions of successive frames. For this purpose, it involves three steps. The first step is to determine a seed point that is the closest point to the center point of a previous frame. The second step is to perform region growing to form a candidate region of a hand. The third step is to determine the center point of a hand to be tracked. This point is searched by the mean-shift algorithm within a confined area whose size varies adaptively according to the depth information. To verify the effectiveness of our approach, we have evaluated the performance of our approach while changing the shape and position of a hand as well as the velocity of hand movement.

• The KIPS Transactions:PartB
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• v.18B no.5
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• pp.255-264
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• 2011

In this paper, we propose a forward vehicle detection algorithm using column detection and bird's-eye view mapping based on stereo vision. The algorithm can detect forward vehicles robustly in real complex traffic situations. The algorithm consists of the three steps, namely road feature-based column detection, bird's-eye view mapping-based obstacle segmentation, obstacle area remerging and vehicle verification. First, we extract a road feature using maximum frequent values in v-disparity map. And we perform a column detection using the road feature as a new criterion. The road feature is more appropriate criterion than the median value because it is not affected by a road traffic situation, for example the changing of obstacle size or the number of obstacles. But there are still multiple obstacles in the obstacle areas. Thus, we perform a bird's-eye view mapping-based obstacle segmentation to divide obstacle accurately. We can segment obstacle easily because a bird's-eye view mapping can represent the position of obstacle on planar plane using depth map and camera information. Additionally, we perform obstacle area remerging processing because a segmented obstacle area may be same obstacle. Finally, we verify the obstacles whether those are vehicles or not using a depth map and gray image. We conduct experiments to prove the vehicle detection performance by applying our algorithm to real complex traffic situations.