• Journal of KIISE:Software and Applications
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• v.34 no.10
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• pp.929-936
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• 2007

The novel vision-based scheme for real-time extracting traffic parameters is proposed in this paper. Detecting and tracking of vehicle is processed at local region installed by operator. Local region is divided to segmented regions by edge and frame difference, and the segmented regions are classified into vehicle, road, shadow and headlight by statistical and geometrical features. Vehicle is detected by the result of the classification. Traffic parameters such as velocity, length, occupancy and distance are estimated by tracking using template matching at local region. Because background image are not used, it is possible to utilize under various conditions such as weather, time slots and locations. It is performed well with 90.16% detection rate in various databases. If direction, angle and iris are fitted to operating conditions, we are looking forward to using as the core of traffic monitoring systems.

• Journal of Korea Water Resources Association
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• v.37 no.7
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• pp.569-579
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• 2004

Recently, the extreme drought is often occurred due to the global warming and the serious weather changes. Also, the problems of the water pollution In the developed areas, the oppositions from people in the upper stream area and water concession from the local governments affect the national request to get more clean water resources in upper stream of the undeveloped areas. It also brings on the necessity of recognition for water supply managements. Therefore, as the water demand is rapidly changes in the metropolitan areas, the capability of water supply from the north Han river basin dams should be appropriately investigated. In this study, we developed a simulation system using STELLA (equation omitted) software environment, a shared vision model, to analyze the possibility of the stable water supply from north Han river basin dams. Also, three different rules are applied on this model by dividing the water level to minimum(Rule 1), medium(Rule 2) and maximum(Rule 3). Using the rules, the safety yield changes are analyzed for dam rule curve of the reservoir and hydropower release.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1264-1274
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• 2015

Human action recognition received many interest in the computer vision community. Most of the existing methods focus on either construct robust descriptor from the temporal domain, or computational method to exploit the discriminative power of the descriptor. In this paper we explore the idea of using local action attributes to form an action descriptor, where an action is no longer characterized with the motion changes in the temporal domain but the local semantic description of the action. We propose an novel framework where introduces local action attributes to represent an action for the final human action categorization. The local action attributes are defined for each body part which are independent from the global action. The resulting attribute descriptor is used to jointly model human action to achieve robust performance. In addition, we conduct some study on the impact of using body local and global low-level feature for the aforementioned attributes. Experiments on the KTH dataset and the MV-TJU dataset show that our local action attribute based descriptor improve action recognition performance.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.23 no.5
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• pp.461-470
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• 2001

A unhealthy 58-year-old male patient required extraction of left upper second molar due to advanced periodontitis. Lidocaine contained 1 : 100000 epinephrine for left posterior superior alveolar nerve block was administered in the mucobuccal fold above the second molar to be treated at the local private dental clinic. After four hours of posterior superior alveolar block anesthesia, patient feeled double vision and discomfort of eyeball movement. At next day, he complained difficulty of left eyeball movement, vertigo and diplopia. He was referred to our department via local clinic and department of ophthalomology of our hospital. He was treated by medication and eyeball exercise, and then follow up check. The double vision and medial rectus muscle palsy disappeared patially after 2 months of block anesthesia. We described herein an ocular complication of diplopia and inferior rectus muscle palsy after posterior superior alveolar nerve block for extraction of left upper second molar, and review the cause or origin of this case. The autonomic nervous system is presented as the logical basis for the untoward systems of ophthalmologic sign likely to diplopia and inferior rectus muscle palsy, rather then simple circulation of anesthetic solution in the vascular network.

• Journal of the Semiconductor & Display Technology
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• v.14 no.4
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• pp.56-60
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• 2015

Mobile devices like smartphones and tablets are becoming increasingly capable in terms of processing power. Although they are already used in computer vision, no comparable measurement experiments of the popular feature extraction algorithm have been made yet. That is, local feature descriptors are widely used in many computer vision applications, and recently various methods have been proposed. While there are many evaluations have focused on various aspects of local features, matching accuracy, however there are no comparisons considering on speed trade-offs of recent descriptors such as ORB, FAST and BRISK. In this paper, we try to provide a performance evaluation of feature descriptors, and compare their matching precision and speed in KD-Tree setup with efficient computation of Hamming distance. The experimental results show that the recently proposed real valued descriptors such as ORB and FAST outperform state-of-the-art descriptors such SIFT and SURF in both, speed-up efficiency and precision/recall.

• Journal of the Semiconductor & Display Technology
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• v.10 no.2
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• pp.31-38
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• 2011

This paper introduces a video based traffic monitoring system for detecting vehicles and obstacles on the road. To segment moving objects from image sequence, we adopt the background subtraction algorithm based on the local binary patterns (LBP). Recently, LBP based texture analysis techniques are becoming popular tools for various machine vision applications such as face recognition, object classification and so on. In this paper, we adopt an extension of LBP, called the Diagonal LBP (DLBP), to handle the background subtraction problem arise in vision-based autonomous parking systems. It reduces the code length of LBP by half and improves the computation complexity drastically. An edge based shadow removal and blob merging procedure are also applied to the foreground blobs, and a pose estimation technique is utilized for calculating the position and heading angle of the moving object precisely. Experimental results revealed that our system works well for real-time vehicle localization and tracking applications.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.75-85
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• 2013

To acquire depth information using stereo vision, it is required to find correspondence points between stereo image pair. Conventional stereo vision systems usually use two cameras to get disparity data. Therefore, conventional stereo matching methods cannot resolve the tradeoff problem between accuracy and precision with respect to the length of baseline. Besides, belief propagation method, which is being used recently, has a problem that matching performance is dependent on the fixed weight parameter ${\lambda}$. In this paper, we propose a modified belief propagation stereo matching technique based on multi-baseline stereo vision to solve the tradeoff problem. The proposed method calculates EMAD(extended mean of absolute differences) as local evidence. And proposed method decides weight parameter ${\lambda}$ adaptively to local texture information. The proposed method shows higher initial matching performance than conventional methods and reached optimum solution in less iteration. The matching performance is increased about 4.85 dB in PSNR.

• Asia-Pacific Journal of Business
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• v.10 no.1
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• pp.87-103
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• 2019

In December 2017, the Moon Jae-in administration announced a major policy shift away from nuclear and coal, committing itself to the vision of creating a society where renewable sources account for 20% of its electricity generation by 2030. This energy transition involves not just a technical transition from conventional energy sources to renewable energy but also active participation of multiple stakeholders in the energy governance. While energy policy making has long been dominated by the central government in Korea with the aim of managing the supply for rapid industrialization and economic growth, the Moon administration aims to diffuse the central government's authority across various actors in society. Among those actors, this study focuses on the roles that local governments play in energy transition. Despite deepening local autonomy since 1995, Korean local governments have remained policy targets or recipients in the energy policy domain. This article discusses how such a traditional role has evolved under the new administration's energy transition policy and examines what challenges and limitations local governments face in creating a more decentralized energy governance system.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.623-628
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• 2008

We present a new method of extracting foreground object from background image for vision-based game interface. Background Subtraction is an important preprocessing step for extracting the features of tracking objects. The image is divided into the cells where the Local Histogram with Gaussian kernel is computed and compared with the corresponding one using Bhattacharyya distance measure. The histogram-based method is partially robust against illumination change, noise and small moving objects in background. We propose a Multi-Scaled Integral Histogram approach for noise suppression and fast computation.

• ETRI Journal
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• v.35 no.6
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• pp.1021-1028
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• 2013

Automatic facial expression recognition is a widely studied problem in computer vision and human-robot interaction. There has been a range of studies for representing facial descriptors for facial expression recognition. Some prominent descriptors were presented in the first facial expression recognition and analysis challenge (FERA2011). In that competition, the Local Gabor Binary Pattern Histogram Sequence descriptor showed the most powerful description capability. In this paper, we introduce hybrid facial representations for facial expression recognition, which have more powerful description capability with lower dimensionality. Our descriptors consist of a block-based descriptor and a pixel-based descriptor. The block-based descriptor represents the micro-orientation and micro-geometric structure information. The pixel-based descriptor represents texture information. We validate our descriptors on two public databases, and the results show that our descriptors perform well with a relatively low dimensionality.