• 한국멀티미디어학회논문지
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• 제12권6호
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• pp.804-814
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• 2009

In this paper, a novel system for avatar motion controlling by tracking face is presented. The system is composed of three main parts: firstly, LCS (Local Cluster Searching) method based face feature detection algorithm, secondly, HMM based feature points recognition algorithm, and finally, avatar controlling and animation generation algorithm. In LCS method, face region can be divided into many small piece regions in horizontal and vertical direction. Then the method will judge each cross point that if it is an object point, edge point or the background point. The HMM method will distinguish the mouth, eyes, nose etc. from these feature points. Based on the detected facial feature points, the 3D avatar is controlled by two ways: avatar orientation and animation, the avatar orientation controlling information can be acquired by analyzing facial geometric information; avatar animation can be generated from the face feature points smoothly. And finally for evaluating performance of the developed system, we implement the system on Window XP OS, the results show that the system can have an excellent performance.

• 한국항만학회지
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• 제14권1호
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• pp.97-105
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• 2000

This paper presents an automatic mesh generation considering water depth, which is based on the depth interpolation. The key feature of this method is that the position of a mesh on any depth in the shallow water area can be generated. The Examples are carried out, and the results are shown to be good. This method is shown to be a useful and powerful tool for the flow calculation for the seabed topography.

• 전자공학회논문지B
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• 제29B권11호
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• pp.102-110
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• 1992

In this paper, a new method of character recognition is proposed. It uses density information, in addition to positional and directional information generally used, to recognize a character. Four directional feature primitives are extracted from the thinning templates on the observation that the output of the templates have directional property in general. A simple and fast feature extraction scheme is possible. Features are organized from recursive nonary tree(N-tree) that corresponds to normalized character area. Each node of the N-tree has four directional features that are sum of the features of it's nine sub-nodes. Every feature primitive from the templates are added to the corresponding leaf and then summed to the upper nodes successively. Recognition can be accomplished by using appropriate feature level of N-tree. Also, effectiveness of each node's feature vector was tested by experiment. A method to implement the proposed feature vector organization algorithm into hardware is proposed as well. The third generation node, which is 4$\times$4, is used as a unit processing element to extract features, and it was implemented in hardware. As a result, we could observe that it is possible to extract feature vector for real-time processing.

• 한국멀티미디어학회논문지
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• 제21권7호
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• pp.755-763
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• 2018

In this paper, for recognize a night pedestrian from an infrared video, a new method differentiated from the existing feature vector is proposed and experimented. The new approach focuses on the shape feature vector of the structure and shape of the pedestrian image divided by the human body seven split ratio. The pedestrian images are divided into 7 square blocks from the still image of the preprocessing process. And to reduce the dimension, the square block is converted into a mosaic block. The scalar and direction of the shape feature vector is calculated by the brightness and position of the element in the mosaic. For practicality of infrared video system, the proposed method simplifies the data to be processed by reducing the amount of data in the preprocessing in order to continuously batch process the entire system in real time. Through the experiments, we verified the validity of the proposed shape feature vector. In comparison to the existing method, we propose a new shape feature vector generation method as the feature vector for night pedestrian recognition.

• Journal of Multimedia Information System
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• 제6권2호
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• pp.91-98
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• 2019

Many researchers have attempted to recognize three-dimensional faces using feature points extracted from two-dimensional facial photographs. However, due to the limit of flat photographs, it is very difficult to recognize faces rotated more than 15 degrees from original feature points extracted from the photographs. As such, it is difficult to create an algorithm to recognize faces in multiple angles. In this paper, it is proposed a new algorithm to recognize three-dimensional face recognition based on feature points extracted from a flat photograph. This method divides into six feature point vector zones on the face. Then, the vector value is compressed and expanded according to the rotation angle of the face to recognize the feature points of the face in a three-dimensional form. For this purpose, the average of the compressibility and the expansion rate of the face data of 100 persons by angle and face zone were obtained, and the face angle was estimated by calculating the distance between the middle of the forehead and the tail of the eye. As a result, very improved recognition performance was obtained at 30 degrees of rotated face angle.

• 대한공간정보학회지
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• 제17권2호
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• pp.133-143
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• 2009

차세대 수치지도 수시갱신 시스템은 효율적인 수시갱신 체계를 구축하고 데이터의 최신성을 유지하며 고품질의 서비스와 효율적 관리를 수행하기 위한 시스템으로 기존 도엽단위의 수치지도 뿐만 아니라 객체 기반 연속 수치지도의 수시갱신이 가능하도록 시스템이 설계되었으며, 이에 따라 개발이 이루어지고 있다. 본 연구에서는 차세대 수치지도 수시갱신 시스템의 활용 방안 제시 및 경쟁력 확보에 기여하고자 차세대 수치지도 수시갱신 시스템에 대하여 객체기반의 연속 수치지도 및 도엽단위 수치지도의 갱신 실험을 수행하여 시스템 운영에 따른 문제점과 개선사항을 제시하였다. 또한 국토지리정보원을 대상으로 시스템 도입에 따른 비용 및 편익에 대한 분석을 수행하여 차세대 수치지도 수시갱신 시스템의 경제성에 대한 분석을 수행하였다.

• 한국멀티미디어학회논문지
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• 제23권8호
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• pp.965-976
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• 2020

We present in this work a segmentation method of E. coli bacterial images generated via phase contrast microscopy using a deep learning based hybrid feature generation. Unlike conventional machine learning methods that use the hand-crafted features, we adopt the denoising autoencoder in order to generate a precise and accurate representation of the pixels. We first construct a hybrid vector that combines original image, difference of Gaussians and image gradients. The created hybrid features are then given to a deep autoencoder that learns the pixels' internal dependencies and the cells' shape and boundary information. The latent representations learned by the autoencoder are used as the inputs of a softmax classification layer and the direct outputs from the classifier represent the coarse segmentation mask. Finally, the classifier's outputs are used as prior information for a graph partitioning based fine segmentation. We demonstrate that the proposed hybrid vector representation manages to preserve the global shape and boundary information of the cells, allowing to retrieve the majority of the cellular patterns without the need of any post-processing.

• Smart Structures and Systems
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• 제25권5호
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• pp.631-641
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• 2020

To meet the urgent requirements of safety surveillance from civil engineering management authorities, this study proposes a refined and efficient approach to generate full-field high-resolution panorama of construction sites using camera-amounted UAV (Unmanned Aerial Vehicle). GPS (Global Position System) information extraction for pre-registration, feature points filtering for efficient registration and optimal seaming line seeking for fusion are performed in sequence to form the full-field panorama generation framework. Advantages of the proposed method are as follows. First, GPS information can sort images for pre-registration, avoiding inefficient repeated pairwise calculations and matching. Second, the feature points are filtered according to the characteristics of the construction site images to reduce the amount of calculation. The proposed framework is validated on a road construction site and results demonstrate that it can generate an accurate and high-quality full-site panorama for the safety supervision in a much efficient manner.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 A
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• pp.149-151
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• 2005

A new approach considering CO2 air pollution constraints in the long-term generation mix is proposed under uncertain circumstances. A characteristic feature of the presented approach in this paper is what effects give the air pollution constraints in long term best generation mix. Best generation mix problem is formulated by linear programming with fuel and construction cost minimization with load growth, reliability (reserve margin rate) and air pollutionconstraints. The proposed method accommodates the operation of pumped-storage generator. It was assumed in this study that the construction planning of the hydro power plants is given separately from the other generation plans. The effectiveness of the proposed approach is demonstrated by applying to the best generation mix problem of KEPCO-system, which contains nuclear, coal, LNG, oil and pumped-storage hydro plant multi-years.

• 대한기계학회논문집
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• 제19권9호
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• pp.2237-2248
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• 1995

In incompressible flow which has multi-length scale, it has a very important effect which dependent variables are used for adaptive grid generation. Among many length scales in incompressible flow, the dependent variables used for the adaptive grid generation should be able to represent the feature of the concerned system. In this paper, by using vorticity and stream function, in addition to velocity components, the smoother and more stable grid generation is possible and these four flow properties represent each scale. The adaptive grid generation for a lid-driven cavity flow with $N_{re}$ =3200 using four flow properties such as velocity components, vorticity, stream function is performed, and the usefulness of using vorticity and stream function as the indicator for adaptive grid generation is shown.