• KIPS Transactions on Software and Data Engineering
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• v.5 no.8
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• pp.369-376
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• 2016

Among various vehicle extraction techniques, OBPCA (Object-Based Point Cloud Analysis) calculates features quickly by coarse-grained rectangles from top-view of the vehicle candidates. However, it uses only a top-view rectangle to detect a vehicle. Thus, it is hard to extract rectangular objects with similar size. For this reason, accuracy issue has raised on the OBPCA method which influences on DEM generation and traffic monitoring tasks. In this paper, we propose a novel method which uses the most distinguishing vertical elevations to calculate additional features. Our proposed method uses same features with top-view, determines new thresholds, and decides whether the candidate is vehicle or not. We compared the accuracy and execution time between original OBPCA and the proposed one. The experiment result shows that our method produces 6.61% increase of precision and 13.96% decrease of false positive rate despite with marginal increase of execution time. We can see that the proposed method can reduce misclassification.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.897-902
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• 2007

인간과 컴퓨터간의 전통적인 인터페이스는 인간이 요구하는 다양한 인터페이스를 제공하지 못한다는 점에서 점차 사용하기 불편하게 되었고 이는 새로운 형태의 인터페이스에 대한 요구로 이어지게 되었다. 본 논문에서는 이러한 추세에 맞추어 카메라를 통해 인간의 손 제스처를 인식하는 새로운 인터페이스를 연구하였다. 손은 자유도가 높고 3차원의 view direction에 의해 형상이 매우 심하게 변한다. 따라서 윤곽선 기반방법과 같은 2차원으로 투영된 영상에서 contour나 edge의 정보로 손 제스처를 인식하는 데는 한계가 있다. 그러나 모델기반 방법은 3차원 정보를 이용하기 때문에 손 제스처를 인식하는데 좋으나 계산량이 많아 실시간으로 처리하기가 쉽지 않다. 이러한 문제점을 해결하기 위해 손 형상에 대한 대규모 데이터베이스를 구성하고 정규화된 공간에서 Feature 간의 연관성을 파악하여 훈련 데이터 모델을 구성하여 비교함으로써 실시간으로 손 포즈를 구별할 수 있다. 이러한 통계적 학습 기반의 알고리즘은 다양한 데이터와 좋은 feature의 검출이 최적의 성능을 구현하는 것과 연관된다. 따라서 배경으로부터 노이즈를 최대한 줄이기 위해 피부의 색상 정보를 이용하여 손 후보 영역을 검출하고 검출된 후보 영역으로부터 HLF(Haar-like Feature)를 이용하여 손 영역을 검출한다. 검출된 손 영역으로부터 패턴 분류 과정을 거쳐 손 포즈를 인식 하게 된다. 패턴 분류 과정은 HLF를 이용하여 손 포즈를 인식하게 되는데 미리 학습된 각 포즈에 대한 HLF를 이용하여 손 포즈를 인식하게 된다. HLF는 Violar가 얼굴 검출에 적용한 것으로 얼굴 검출에 좋은 결과를 보여 주었으며, 이는 적분 이미지로부터 추출한 HLF를 이용한 Adaboost 학습 알고리즘을 사용하였다. 본 논문에서는 피부색의 색상 정보를 이용 배경과 손 영상을 최대한 분리하여 배경의 대부분이 Adaboost-Haar Classifier의 첫 번째 스테이지에서 제거되는 방법을 이용하여 그 성능을 더 향상 시켜 손 형상 인식에 적용하였다.

• Journal of Korea Game Society
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• v.9 no.1
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• pp.93-103
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• 2009

A Serious Game helps the learners to recognize the problems effectively, grasp and classify important information needed to solve the problems and convey the contents of what they have learned. Owing not only to this game-like fun but also to the educational effect, The Serious Game can be usefully applied to education and training in the areas of scientific technology and industrial technology. This study proposes the Serious Game that users can apply to biotechnology by using intuitive multi-modal interfaces. In this study, a stereoscopic monitor is used to make three dimensional molecular structures, and multi-modal interface is used to efficiently control. Based on a such system, this study easily solved the docking simulation function, which is one of the important experiments, by applying these game factors. For this, we suggested the level-up concept as a game factor that depends on numbers of objects and users. The proposed system was evaluated in performance comparison in result time of a new drug design process on AIDS virus with previous approach.

• Journal of the Korea Society of Computer and Information
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• v.16 no.10
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• pp.93-100
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• 2011

The necessity of research on extracting information of face and facial components in animation characters have been increasing since they can effectively express the emotion and personality of characters. In this paper, we introduce a method to extract face and facial components of animation characters by defining a mesh model adequate for characters and by using dominant colors. The suggested algorithm first generates a mesh model for animation characters, and extracts dominant colors for face and facial components by adapting the mesh model to the face of a model character. Then, using the dominant colors, we extract candidate areas of the face and facial components from input images and verify if the extracted areas are real face or facial components by means of color similarity measure. The experimental results show that our method can reliably detect face and facial components of animation characters.

• 한국해양학회지
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• v.13 no.1
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• pp.29-34
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• 1978

Simultaneous tidal current observation at five or seven stations on the channel near Incheon Habour was conducted at neap, mean and spring tides during the period of August 16 to August 27, 1976 and the characteristic of tidal currents with each tide was studied by the analysis of these data. Times of slack refer to the times of high and low waters at neap, mean and spring tides seem to be small. Times of maximum current refer to the times of high and low waters at the mean tide tends to appear earlier than that of the neap tide and later than that of the spring tide. The velocity ratio of maximum ebb current to maximum flood current at the mean tide has larger value than that of neap tide and has smaller value than that of spring tide. The current velocity ratio of spring tide to neap tide and to mean tide are approximately 1.8 and 1.3, respectively.

• Smart Media Journal
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• v.4 no.4
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• pp.18-23
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• 2015

In this paper, we propose a method for detecting the number of clusters. This method can improve the performance of a gaussian mixture model function in conventional markov random field method by using the tensor voting. The key point of the proposed method is that extracts the number of the center through the continuity of saliency map of the input data of the tensor voting token. At first, we separate the foreground and background region candidate in a given natural images. After that, we extract the appropriate cluster number for each separate candidate regions by applying the tensor voting. We can make accurate modeling a gaussian mixture model by using a detected number of cluster. We can return the result of natural binary text image by calculating the unary term and the pairwise term of markov random field. After the experiment, we can confirm that the proposed method returns the optimal cluster number and text binarization results are improved.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10C
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• pp.1010-1015
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• 2009

In this paper, we propose a novel detection ordering technique for MIMO signal detection methods based on QR decomposition and successive interference cancellation (SIC). Recently, new signal detection methods for spatially multiplexed (SM) MIMO systems were proposed, where all the constellation points are tried as the first layer symbol, and the remaining layer symbols are estimated via SIC, producing candidate vectors. Finally, the ML metric values are calculated for the candidate vectors, that are again used to select the best symbol vector. It was also shown that the ordering method in the conventional V-BLAST is not suitable to these signal detection methods. In this paper, we propose a novel ordering method, and we show via computer simulations that the proposed ordering method improves the error performance.

• Journal of Digital Contents Society
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• v.7 no.1
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• pp.67-74
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• 2006

In current video-conferencing systems. user's face movements are restricted by fixed camera, therefore it is inconvenient to users. To solve this problem, tracking of face movements is needed. Tracking using whole face needs much computing time and whole face is difficult to define as an one feature. Thus, using several feature points in face is more desirable to track face movements efficiently. This paper addresses an effective eye location algorithm which is essential process of automatic human face tracking system for natural video-conferencing. The location of eye is very important information for face tracking, as eye has most clear and simplest attribute in face. The proposed algorithm is applied to candidate face regions from the face region extraction. It is not sensitive to lighting conditions and has no restriction on face size and face with glasses. The proposed algorithm shows very encouraging results from experiments on video-conferencing environments.

• The KIPS Transactions:PartB
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• v.11B no.2
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• pp.149-158
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• 2004

This study proposes a method for segmentation and recognition of traffic signs using shape information and edge image in real image. It first segments traffic sign candidate regions by connected component algorithm from binary images, obtained by utilizing the RGB color ratio of each pixel in the image, and then extracts actual traffic signs based on their symmetries on X- and Y-axes. Histogram equalization is performed for unsegmented candidate regions caused by low contrast in the image. In the recognition stage, it utilizes shape information including projection profiles on X- and Y-axes, moment, and the number of crossings and distance which concentric circular patterns and 8-directional rays from region center intersects with edges of traffic signs. It finally performs recognition by measuring similarity with the templates in the database. It will be shown from several experimental results that the system is robust to environmental factors, such as light and weather condition.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.77-84
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• 2008

This paper proposes a new approach to eliminate the reflectance component for the localization of text in natural scene images. Natural scene images normally have an illumination component as well as a reflectance component. It is well known that a reflectance component usually obstructs the task of detecting and recognizing objects like texts in the scene, since it blurs out an overall image. We have developed an approach that efficiently removes reflectance components while Preserving illumination components. We decided whether an input image hits Normal or Polarized for determining the light environment, using the histogram which consisted of a red component. In the normal image, we acquired the text region without additional processing. Otherwise we removed light reflecting from the object using homomorphic filtering in the polarized image. And then this decided the each text region based on the color merging technique and the Saliency Map. Finally, we localized text region on these two candidate regions.