• Korean Journal of Remote Sensing
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• v.22 no.3
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• pp.221-228
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• 2006

In this study, an integrated 3D modeling and rendering system dealing with 3D urban landscape features such as terrain, building, road and user-defined geometric ones was designed and implemented using $OPENGL\;{|}\;ES$ (Embedded System) API for mobile devices of PDA. In this system, the authoring functions are composed of several parts handling urban landscape features: vertex-based geometry modeling, editing and manipulating 3D landscape objects, generating geometrically complex type features with attributes for 3D objects, and texture mapping of complex types using image library. It is a kind of feature-based system, linked with 3D geo-based spatial feature attributes. As for the rendering process, some functions are provided: optimizing of integrated multiple 3D landscape objects, and rendering of texture-mapped 3D landscape objects. By the active-synchronized process among desktop system, OPENGL-based 3D visualization system, and mobile system, it is possible to transfer and disseminate 3D feature models through both systems. In this mobile 3D urban processing system, the main graphical user interface and core components is implemented under EVC 4.0 MFC and tested at PDA running on windows mobile and Pocket Pc. It is expected that the mobile 3D geo-spatial information systems supporting registration, modeling, and rendering functions can be effectively utilized for real time 3D urban planning and 3D mobile mapping on the site.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.7
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• pp.1437-1443
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• 2009

This paper is presented an simultaneous localization and mapping (SLAM) algorithm using ultrasonic for robot and electric compass, encoder, and gyro. Generally, localization based upon electric compass, encoder, and gyro can be measured just local position in workspace. However, actual robot must need an information of the absolute position in workspace to perform its mission, Absolute position in workspace could be calculated using SLAM algorithm. To implement SLAM in this paper, a map is built using ultrasonic sensor and hierarchical map building method. And then, we the map will be transformed into a feature map. The absolute position could be calculated using the feature map and map mapping method. As a test bed, we designed and construct an autonomous robot and showed the experimental performance of the proposed SLAM algorithm based on feature map. Experimental result, we verified that robot can found all absolute position on experiments using proposed SLAM algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.105-110
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• 2014

Feature-oriented software product line engineering is to develop various products by developing product line core assets in terms of features and composing those features. However, the developed product may not behave correctly if the feature interaction problem has not be properly taken into account during the feature composition. This paper proposes techniques for identifying and modularizing undesirable feature interactions effectively. The scientific calculator product line is used for evaluating the applicability of the proposed method.

• Korean Journal of Cognitive Science
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• v.14 no.1
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• pp.10-10
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• 2003

This paper extracts the edge of main components of face with Gabor wavelets transformation in facial expression images. FCM(Fuzzy C-Means) clustering algorithm then extracts the representative feature points of low dimensionality from the edge extracted in neutral face. The feature-points of the neutral face is used as a template to extract the feature-points of facial expression images. To match point to Point feature points on an expression face against each feature point on a neutral face, it consists of two steps using a dynamic linking model, which are called the coarse mapping and the fine mapping. This paper presents an automatic extraction of feature-points by dynamic linking model based on Gabor wavelets and fuzzy C-means(FCM) algorithm. The result of this study was applied to extract features automatically in facial expression recognition based on dimension[1].

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.5
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• pp.277-282
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• 2003

In this paper we propose Using Higher Order Neuron on the Supervised Learning Machine of the Kohonen Feature Map. The architecture of proposed model adopts the higher order neuron in the input layer of Kohonen Feature Map as a Supervised Learning Machine. It is able to estimate boundary on input pattern space because or the higher order neuron. However, it suffers from a problem that the number of neuron weight increases because of the higher order neuron in the input layer. In this time, we solved this problem by placing the second order neuron among the higher order neuron. The feature of the higher order neuron can be mapped similar inputs on the Kohonen Feature Map. It also is the network with topological mapping. We have simulated the proposed model in respect of the recognition rate by XOR problem, discrimination of 20 alphabet patterns, Mirror Symmetry problem, and numerical letters Pattern Problem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.3984-4005
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• 2017

Image recognition has become an increasingly important topic for its wide application. It is highly challenging when facing to large-scale database with large variance. The recognition systems rely on a key component, i.e. the low-level feature or the learned mid-level feature. The recognition performance can be potentially improved if the data distribution information is exploited using a more sophisticated way, which usually a function over hidden variable, model parameter and observed data. These methods are called generative score space. In this paper, we propose a discriminative extension for the existing generative score space methods, which exploits class label when deriving score functions for image recognition task. Specifically, we first extend the regular generative models to class conditional models over both observed variable and class label. Then, we derive the mid-level feature mapping from the extended models. At last, the derived feature mapping is embedded into a discriminative classifier for image recognition. The advantages of our proposed approach are two folds. First, the resulted methods take simple and intuitive forms which are weighted versions of existing methods, benefitting from the Bayesian inference of class label. Second, the probabilistic generative modeling allows us to exploit hidden information and is well adapt to data distribution. To validate the effectiveness of the proposed method, we cooperate our discriminative extension with three generative models for image recognition task. The experimental results validate the effectiveness of our proposed approach.

• The Journal of the Korea Contents Association
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• v.13 no.6
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• pp.55-66
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• 2013

In these days, small devices like smartphones, TV, and projectors are popular, and they are being developed rapidly. The projector is being used in cinema and exhibition because it makes a big screen. This feature makes new expression named projection-mapping in art world. Projection-mapping is being utilized extensively in stages of performances, and it use variety of shape's screens. But projection-mapping has limitation in space. So in this paper, we propose new performance system for projection-mapping and it make possible to overcome many difficulties. Also, we discuss the result of using the system in actual performance. We hope to develop the utilization of projection-mapping in performance.

• ETRI Journal
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• v.36 no.6
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• pp.913-923
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• 2014

This paper proposes a global mapping algorithm for multiple robots from an omnidirectional-vision simultaneous localization and mapping (SLAM) approach based on an object extraction method using Lucas-Kanade optical flow motion detection and images obtained through fisheye lenses mounted on robots. The multi-robot mapping algorithm draws a global map by using map data obtained from all of the individual robots. Global mapping takes a long time to process because it exchanges map data from individual robots while searching all areas. An omnidirectional image sensor has many advantages for object detection and mapping because it can measure all information around a robot simultaneously. The process calculations of the correction algorithm are improved over existing methods by correcting only the object's feature points. The proposed algorithm has two steps: first, a local map is created based on an omnidirectional-vision SLAM approach for individual robots. Second, a global map is generated by merging individual maps from multiple robots. The reliability of the proposed mapping algorithm is verified through a comparison of maps based on the proposed algorithm and real maps.

• Korean Journal of Computational Design and Engineering
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• v.9 no.3
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• pp.226-237
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• 2004

If the topology changes in the re-generation step of the history-based and feature-based CAD systems, it is difficult to identify an entity in the old model and find the same entity in the new model. This problem is known as 'persistent naming problem'. To exchange parametric CAD models, the persistent naming problem and the naming mapping problem must be solved among different CAD system, which use different naming scheme. For CAD model exchange the persistent naming has its own characteristics compare to that for CAD system development. This paper analyses previous researches and proposes a solution to the persistent naming problem for CAD model exchanges and to the naming mapping problem among different naming schemes.

• Journal of the Korean Graphic Arts Communication Society
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• v.20 no.2
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• pp.119-129
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• 2002

On the process of cross-media color reproduction, a key feature is the use of gamut mapping techniques to adjust the different color gamuts between displays and printers. Even though a nunber of gamut mapping algorithms were published in the past, only limited colorimetric evaluation of them has been carried out to date. In this paper, the multi-anchor points clipping method(MAPC) was proposed as a new gamut mapping algorithm compensating the defects of the current algorithms such as nearest point clipping method(NPC), centroid clipping method(SLIN), straight clipping method(LLIN) and maximum chroma clipping method(CUSP).