• KIPS Transactions on Software and Data Engineering
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• v.4 no.12
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• pp.585-588
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• 2015

The technical challenge of 3D image display using the wireless sensor were applied to variable areas and scopes. This techniques need to very accurate location and speed informations and recognitions to moving objects. The tracking challenges of the moving objects location that combined 3D location and speed sensor were applied to sports and healthcare areas. This areas seek to the accuracy and collections and tightly related to image display and analysis techniques. In this paper, We developed the 3D motion display that can be monitor moving objects on the 3D virtual space. For this works, we constructed the database that collected informations through 9-axis sensor and demonstrated the result of 3D motion display on the Window based environments.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.667-674
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• 2007

Facial expressions provide significant clues about one's emotional state; however, it always has been a great challenge for machine to recognize facial expressions effectively and reliably. In this paper, we report a method of feature-based adaptive motion energy analysis for recognizing facial expression. Our method optimizes the information gain heuristics of ID3 tree and introduces new approaches on (1) facial feature representation, (2) facial feature extraction, and (3) facial feature classification. We use minimal reasonable facial features, suggested by the information gain heuristics of ID3 tree, to represent the geometric face model. For the feature extraction, our method proceeds as follows. Features are first detected and then carefully "selected." Feature "selection" is finding the features with high variability for differentiating features with high variability from the ones with low variability, to effectively estimate the feature's motion pattern. For each facial feature, motion analysis is performed adaptively. That is, each facial feature's motion pattern (from the neutral face to the expressed face) is estimated based on its variability. After the feature extraction is done, the facial expression is classified using the ID3 tree (which is built from the 1728 possible facial expressions) and the test images from the JAFFE database. The proposed method excels and overcomes the problems aroused by previous methods. First of all, it is simple but effective. Our method effectively and reliably estimates the expressive facial features by differentiating features with high variability from the ones with low variability. Second, it is fast by avoiding complicated or time-consuming computations. Rather, it exploits few selected expressive features' motion energy values (acquired from intensity-based threshold). Lastly, our method gives reliable recognition rates with overall recognition rate of 77%. The effectiveness of the proposed method will be demonstrated from the experimental results.

• Journal of Internet Computing and Services
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• v.10 no.4
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• pp.1-11
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• 2009

Recently there has arisen concern in both the database community and the graphics society about data retrieval from large motion databases because the high dimensionality of motion data implies high costs. In this circumstance, finding an effective distance measure and an efficient query processing method for such data is a challenging problem. This paper presents an elaborate motion query processing system, SMoFinder (Similar Motion Finder), which incorporates a novel kinematic distance measure and an efficient indexing strategy via adaptive frame segmentation. To this end, we regard human motions as multi-linkage kinematics and propose the weighted Minkowski distance metric. For efficient indexing, we devise a new adaptive segmentation method that chooses representative frames among similar frames and stores chosen frames instead of all frames. For efficient search, we propose a new search method that processes k-nearest neighbors queries over only representative frames. Our experimental results show that the size of motion databases is reduced greatly (${\times}1/25$) but the search capability of SMoFinder is equal to or superior to that of other systems.

• Journal of the Korea Computer Graphics Society
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• v.21 no.1
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• pp.23-31
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• 2015

We present a method for creating realistic 2D stick figure animations easily and rapidly using captured motion data. Stick figure animations are typically created by drawing a single pose for each frame manually for the entire time interval. In contrast, our method allows the user to summarize an action (e.g. kick, jump) for an extended period of time into a single image in which one or more action lines are drawn over a stick figure to represent the moving directions of body parts. In order to synthesize a series of time-varying poses automatically from the given image, our system first builds a deformable character model that can make arbitrary deformations of the user's stick figure drawing in 2D plane. Then, the system searches for an optimal motion segment that best fits the given pose and action lines from pre-recorded motion database. Deforming the character model to imitate the retrieved motion segment produces the final stick figure animation. We demonstrate the usefulness of our method in creating interesting stick figure animations with little effort through experiments using a variety of stick figure styles and captured motion data.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.958-963
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• 2023

Lately, there has been increasing research on the prediction of motion performance using artificial intelligence for the safe design and operation of ships. However, compared to conventional ships, research on small fishing boats is insufficient. In this paper, we propose a model that estimates the motion response essential for calculating the motion performance of small fishing boats using a deep neural network. Hydrodynamic analysis was conducted on 15 small fishing boats, and a database was established. Environmental conditions and main particulars were applied as input data, and the response amplitude operators were utilized as the output data. The motion response predicted by the trained deep neural network model showed similar trends to the hydrodynamic analysis results. The results showed that the high-frequency motion responses were predicted well with a low error. Based on this study, we plan to extend existing research by incorporating the hull shape characteristics of fishing boats into a deep neural network model.

• Journal of the Earthquake Engineering Society of Korea
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• v.16 no.1
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• pp.37-45
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• 2012

In an effort to further exploit the peak ground-motion acceleration (PGA) information per second available in real time by the enacted law, bracketed summations of the PGA per second ($BSPGA_k$) for 30 seconds based on the records with a rate of 100 samples were compared with the cumulative absolute velocity (CAV) and earthquake intensities based on a worldwide database of records from small-to-large earthquakes. The CAV, currently in use as an earthquake damage indicator for nuclear power plants due to its strong correlation with the earthquake intensity, has the disadvantage of requiring a massive amount of digital data with a rate of more than 100 samples per second. The comparative study shows that the $BSPGA_k$ is well correlated with the CAV over the wide range of strong ground-motion levels, which suggests that the $BSPGA_k$ is one of the new promising ground-motion parameters especially useful for rapid earthquake alert notifications through an earthquake monitoring network. Based on the domestic database of records from small-to-moderate earthquakes with felt reports, it is also observed that the $BSPGA_k$ is comparable to the CAV and better than the PGA in predicting the intensity by using the correlation relation.

• Journal of Digital Contents Society
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• v.19 no.2
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• pp.319-325
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• 2018

The general public's interest in dementia has increased recently as dementia has become a social issue due to its rapid aging. Several dementia prevention and rehabilitation programs are being carried out at the dementia rehabilitation center and at the old welfare center depending on the number of dementia patients. In this paper, a 3 dimensional finger and motion search of the leap motion is utilized and combined with dementia preventive and cognitive rehabilitation programs at various facilities. We suggest technologies that can provide both fun and effective treatment and rehabilitation content for rehabilitation therapists. A variety of cognitive enhancement content is designed using finger tracking and configured to be recorded in the database for rehabilitation programmes to increase the effectiveness of management.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.9 s.180
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• pp.2259-2265
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• 2000

A dynamic modeling of a rotating pretwist blade which interacts with the fluid is proposed in this study. The hybrid deformation variable modeling method is employed to derive the equations of motion. The external force and moment induced by the fluid (with fixed configurations of the blade) are obtained by fluid flow analysis and tabulated in a database. This database is efficiently utilized to save the computational effort to calculate the dynamic response of the blade. The numerical results show that the fluid affects the transient response as well as frequency characteristics of the system.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.06a
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• pp.137-142
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• 1997

One of the inherent problems in constructing the sign language dictionary is how to make retrieval and comparison operations on the visual database of signs. This paper describes a retrieval method, especifically for Japanese signs. This method has a useful capability for flexible retrieval of the sign from a bilingual dictionary. Our method can retrieve similar signs to the given input. The retrieval mechanism is essentially based on similarity between the given verbal description and verbal descriptions in a retrieval database. The similarity measure of verbal descriptions can be considered as the approximations for the similarity of sign motion images. As a results of our experiment, the success ratio of the retrievals is 96% in averages.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.3
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• pp.175-181
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• 1993

In this paper, a practical method to generate task strategies applicable to chamferless and high-precision assembly, is proposed. The difficulties in devising reliable assembly strategies result from various forms of uncertainty such as imperfect knowledge on the parts being assembled and functional limitations of the assembly devices. In approach to cope with these problems, the robot is provided with the capability of learning the corrective motion in response to the force signal trrough iterative task execution. The strategy is realized by adopting a learning algorithm and represented in a binary tree type database. To verify the effectiveness of the proposed algorithm, a series of simulations and experiments are carried out under assimilated real production environments. The results show that the sensory signal-to-robot action mapping can be acquired effectively and, consequently, the chamferless assembly can be performed successfully.