• IMMUNE NETWORK
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• v.7 no.1
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• pp.26-30
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• 2007

Background: Mycobacterial antigens released as PIM, LM, LAM, lipoproteins and other cellular factors may contribute to macrophage and dendritic cell activation through pattern recognition receptors such as TLRs. In this study, we assessed cytokine production and ERK activation with stimulation of several major mycobacterial antigens. Methods: Purified mycobacterial antigens (10, 22, 30, 38kDa) and recombinant antigens (6, 16, 19, 38kDa, Ag85A antigen) were studied. The production of cytokines (TNF-${\alpha}$, IL-12, IL-6) was measured by ELISA. The ERK activation was detected by western blotting. The expression of TLR2 or TLR4 was measured by flow cytometry. Results: Among purified antigens only 30kDa antigen induced production of IL-6 or TNF-${\alpha}$ in THP-1 macrophage cells. When THP-1 macrophage cells were treated with 30kDa antigen, phosphorylation of ERK was detected. ERK activation also occurred in TLR2 transfectant HEK293 cells with 30kDa antigen stimulation. Conclusion: 30kDa antigen is one of the major mycobacterial antigens inducing cytokine production and MAP kinases phosphorylation in macrophages.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.4
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• pp.377-385
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• 2015

This paper proposes a novel forward vehicle tracking algorithm based on the WMIL(Weighted Multiple Instance Learning) equipped with a particle filter. In the proposed algorithm Haar-like features are used to train a vehicle object detector to be tracked and the location of the object are obtained from the recognition result. In order to combine both the WMIL to construct the vehicle detector and the particle filter, the proposed algorithm updates the object location by executing the propagation, observation, estimation, and selection processes involved in particle filter instead of finding the credence map in the search area for every frame. The proposed algorithm inevitably increases the computation time because of the particle filter, but the tracking accuracy was highly improved compared to Ababoost, MIL(Multiple Instance Learning) and MIL-based ones so that the position error was 4.5 pixels in average for the videos of national high-way, express high-way, tunnel and urban paved road scene.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6C
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• pp.593-603
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• 2009

In this paper, we propose a new integrated computer vision system designed to track multiple human beings and extract their silhouette with an active stereo camera. The proposed system consists of three modules: detection, tracking and silhouette extraction. Detection was performed by camera ego-motion compensation and disparity segmentation. For tracking, we present an efficient mean shift based tracking method in which the tracking objects are characterized as disparity weighted color histograms. The silhouette was obtained by two-step segmentation. A trimap is estimated in advance and then this was effectively incorporated into the graph cut framework for fine segmentation. The proposed system was evaluated with respect to ground truth data and it was shown to detect and track multiple people very well and also produce high quality silhouettes. The proposed system can assist in gesture and gait recognition in field of Human-Robot Interaction (HRI).

• Archives of design research
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• v.19 no.1 s.63
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• pp.79-88
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• 2006

A human face figure is a visual symbol of identity. Each different face per person is a critical information differentiating each person from others and it directly relates to individual identity. When we look back human history, historical change of recognition for a face led to the change of expression and communication media and it in turn caused many changes in expressing a face. However, there has not been no time period when people pay attention to a face more than this time. Technically, the advent of computer graphics opened new turning point in expressing human face figure. Especially, a visual image which can be produced, saved, and transferred in digital has no limitation in time and space, and its importance in communication is getting higher and higher. Among those visual image information, a face image in digital is getting more applications. Therefore, 3d (3-dimensional) expression of a face using computer graphics can be easily produced without any professional techniques, just like assembling puzzle parts composed of the shape of each part ands texture map, etc. This study presents a method with which a general visual designer can effectively express 3d type face by studying each producing step of 3d face expression and by visualizing case study based on the above-mentioned study result.

• Korean Journal of Cognitive Science
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• v.22 no.2
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• pp.103-121
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• 2011

This study investigated how spatial dimension information and dimensional consistency between learning and testing phase would influence the target search performance. The participants learned spatial layouts of Lego blocks shown in either two- (2D) or three-dimension (3D) and were tested with the rotated stimuli ($0^{\circ}$, $90^{\circ}$, $180^{\circ}$, or $270^{\circ}$ from the initial view) in consistent or inconsistent dimension. Significantly better performance was observed when initial learning display appeared in 2D than in 3D. Particularly, the participants showed difficulties in flexible usage of spatial information presented in 3D especially if the dimensional information in the testing phase also was 3D and required mental rotation. The present study indicates that spatial map presented in 2D may be more useful than 3D in driving situations in which acquired spatial information from navigating device, such as GPS, and location of driver continuously changes.

• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.484-491
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• 2015

Aerial scene is greatly increased by the introduction and supply of the image due to the growth of digital optical imaging technology and development of the UAV. It has been used as the extraction of ground properties, classification, change detection, image fusion and mapping based on the aerial image. In particular, in the image analysis and utilization of deep learning algorithm it has shown a new paradigm to overcome the limitation of the field of pattern recognition. This paper presents the possibility to apply a more wide range and various fields through the segmentation and classification of aerial scene based on the Deep learning(ConvNet). We build 4-classes image database consists of Road, Building, Yard, Forest total 3000. Each of the classes has a certain pattern, the results with feature vector map come out differently. Our system consists of feature extraction, classification and training. Feature extraction is built up of two layers based on ConvNet. And then, it is classified by using the Multilayer perceptron and Logistic regression, the algorithm as a classification process.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.102-108
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• 2011

Support vector machines are well known for their outstanding performance in pattern recognition fields. One example of their applications is music/speech classification for a standardized codec such as 3GPP2 selectable mode vocoder. In this paper, we propose a novel scheme that improves the speech/music classification of support vector machines based on the second-order conditional maximum a priori. While conventional support vector machine optimization techniques apply during training phase, the proposed technique can be adopted in classification phase. In this regard, the proposed approach can be developed and employed in parallel with conventional optimizations, resulting in synergistic boost in classification performance. According to experimental results, the proposed algorithm shows its compatibility and potential for improving the performance of support vector machines.

• Journal of Forest and Environmental Science
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• v.33 no.3
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• pp.187-196
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• 2017

The use of unmanned aerial vehicles (UAV) for the estimation of tree height is gaining recognition. This study aims to assess the effectiveness of tree height estimation of Pinus densiflora Sieb. et Zucc. and Pinus koraiensis Sieb. et Zucc. using digital surface model (DSM) generated from UAV-acquired imageries. Images were taken with the $Trimble^{(R)}$ UX5 equipped with Sony ${\alpha}5100$. The generated DSM, together with the digital elevation model (DEM) generated from a digital map of the study areas, were used in the estimation of tree height. Field measurements were conducted in order to generate a regression model and carry out accuracy assessment. The obtained coefficients of determination (R2) and root mean square error (RMSE) for P. densiflora (R2=0.71; RMSE=1.00 m) and P. koraiensis (R2=0.64; RMSE=0.85 m) are comparable to the results of similar studies. The results of the paired two-tailed t-test show that the two tree height estimation methods are not significantly different (p-value=0.04 and 0.10, alpha level=0.01), which means that tree height estimation using UAV imagery could be used as an alternative to field measurement.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.29 no.1
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• pp.479-485
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• 2005

Recently the spread which RFID technology is overcomes the limit of existing recognition technology, it is forecast with the fact that it will bring a new renovation at the business and the industrial all over. Specially the case RFID technology of Port Logistic Industry will be applied it is forecast with the fact that it will bring a many effect. The government leads introduces a RFID technology of Port Logistic Industry through the various demonstration business. But it is many with the research insufficient the depression against an actuality improvement subject and the depression of technical know-how strategy and it is difficult it is undergoing. In order to solve this problems, we propose an introduction of technical know-how Road Map that we select ranking with Existing literature investigation and the present business demand anaylsis. In the future this research it it forecast in future the successful guide line to the RFID technology introduction of Port Logistic Industry will become.

• Journal of Korea Game Society
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• v.8 no.2
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• pp.25-35
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• 2008

Seunglamdonoli was a traditional board game played during the Chosun Dynasty. In this article, I interpret its features as a board game and discuss the possibility of turning it into a mass market game like Milton Bradley's 'The Game of Life' in the U.S. Seunglamdonoli uses the dice to determine movements around a board shaped like Korea, teaching players about important geographic locations, and traditional characters in a game that relies on strategy as well as luck. With appropriate changes such as introducing a standardized game board or digitalization for use on computers, Seunglamdonoli has potential to again become a popular pastime as well as become tool for learning about Korean history, geography, and society. Furthermore it can be adapted as an educational game for any location with minimal changes.