• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.119-128
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• 2014

In this paper, a fast human detection method using adaptive UV-histogram and template matching is proposed. The proposed method improves the detection rate in the scene of complex environment. The method firstly generates U-histogram to extract human candidates and adaptively generates V-histogram for each labled U-histogram, thus it could extract humans correctly, which was impossible in the previous method. The method tries to match the human candidates with the adaptively sized omega shape template to the focal length and distance in order to improve the detection accuracy. It also detects false positives by rematching the template with accumulated foreground images and hence is robust to the occlusion. Experimental results showed that the proposed method has superior performance to the Bae's method in the complex environment with about 15% improvement in precision and 80% in recall and has 20 times faster processing time than Xia's method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.6
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• pp.1312-1317
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• 2003

This paper presents an integrated approach to unconstrained face recognition in arbitrary scenes. The front end of the system comprises of a scale and pose tolerant face detector. Scale normalization is achieved through novel combination of a skin color segmentation and log-polar mapping procedure. Principal component analysis is used with the multi-view approach proposed in[10] to handle the pose variations. For a given color input image, the detector encloses a face in a complex scene within a circular boundary and indicates the position of the nose. Next, for recognition, a radial grid mapping centered on the nose yields a feature vector within the circular boundary. As the width of the color segmented region provides an estimated size for the face, the extracted feature vector is scale normalized by the estimated size. The feature vector is input to a trained neural network classifier for face identification. The system was evaluated using a database of 20 person's faces with varying scale and pose obtained on different complex backgrounds. The performance of the face recognizer was also quite good except for sensitivity to small scale face images. The integrated system achieved average recognition rates of 87% to 92%.

• Journal of the Society of Disaster Information
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• v.12 no.4
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• pp.342-349
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• 2016

The objectives of this study is analysis of the characteristics of fire risk and survey of narrow dwelling space(the Karaoke, Gosiwon etc). The narrow dwelling space has special structure characteristics; the narrow and the complex escape rote. Gosiwon have very separate and exclusive space room, so have the problem a suppression of fire. Furthermore almost Karaokes located in basement have a complex and limitary escape rote. Therefore we should research and development the exploration equipment that search a source of the fire and a emergency rescuer in the scene of the fire.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.5
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• pp.162-170
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• 2004

In these days, a vehicle simulator is developed by using a VR(Virtual Reality) system. A VR system must provide a vehicle simulator with a natural interaction, a sufficient immersion and realistic images. To achieve this, it is important to provide a fast and uniform rendering performance regardless of the complexity of virtual worlds or the level of simulation. In this paper, modeling methods which offer an improved rendering performance for complex VR applications as 3D road model have been implemented and verified. The key idea of the methods is to reduce a load of VR system by means of LOD(Level of Detail), alpha blending texture mapping, texture mip-mapping and bilboard. Hence, in 3D road model where a simulation is complex or a scene is very large, the methods can provide uniform and acceptable frame rates. The VR system which is constructed with the methods has been experimented under the various application environments. It is confirmed that the proposed methods are effective and adequate to the VR system which associates with a vehicle simulator.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.311-326
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• 2024

The rapid development of neural network technology promotes the neural network model driven by big data to overcome the texture effect of complex objects. Due to the limitations in complex scenes, it is necessary to establish custom template matching and apply it to the research of many fields of computational vision technology. The dependence on high-quality small label sample database data is not very strong, and the machine learning system of deep feature connection to complete the task of texture effect inference and speculation is relatively poor. The style transfer algorithm based on neural network collects and preserves the data of patterns, extracts and modernizes their features. Through the algorithm model, it is easier to present the texture color of patterns and display them digitally. In this paper, according to the texture effect reasoning of custom template matching, the 3D visualization of the target is transformed into a 3D model. The high similarity between the scene to be inferred and the user-defined template is calculated by the user-defined template of the multi-dimensional external feature label. The convolutional neural network is adopted to optimize the external area of the object to improve the sampling quality and computational performance of the sample pyramid structure. The results indicate that the proposed algorithm can accurately capture the significant target, achieve more ablation noise, and improve the visualization results. The proposed deep convolutional neural network optimization algorithm has good rapidity, data accuracy and robustness. The proposed algorithm can adapt to the calculation of more task scenes, display the redundant vision-related information of image conversion, enhance the powerful computing power, and further improve the computational efficiency and accuracy of convolutional networks, which has a high research significance for the study of image information conversion.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.119-126
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• 2003

The problem of tracking moving objects in a video stream is discussed in this pa-per. We discussed the popular technique of optical flow for moving object detection. Optical flow finds the velocity vectors at each pixel in the entire video scene. However, optical flow based methods require complex computations and are sensitive to noise. In this paper, we proposed a new method based on the Hough transform and on voting accumulation for improving the accuracy and reducing the computation time. Further, we applied the Boo-lean based edge detector for edge detection. Edge detection and segmentation are used to extract the moving objects in the image sequences and reduce the computation time of the CHT. The Boolean based edge detector provides accurate and very thin edges. The difference of the two edge maps with thin edges gives better localization of moving objects. The simulation results show that the proposed method improves the accuracy of finding the optical flow vectors and more accurately extracts moving objects' information. The process of edge detection and segmentation accurately find the location and areas of the real moving objects, and hence extracting moving information is very easy and accurate. The Combinatorial Hough Transform and voting accumulation based optical flow measures optical flow vectors accurately. The direction of moving objects is also accurately measured.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.5
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• pp.1201-1209
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• 2008

In Seoul, there are lots of skyscrapers that have above 60 stories and buildings that have more than 8 basement levels, as well as massive distribution complex region which is connected to subways, departments, malls, hotels, and exhibition halls. When an accident, such as fire and explosion, happens in these areas or structures, if we can't find where fire-fighters are, who go into the building to suppress the fire, we couldn't be sure of their safety as well as effective command. Actually, it may cause much more damage itself and restrict either fire suppression or lifesaving. To protect people's life and properties as much as possible, this study will show the method to construct system of disaster-management supports with effective operation of fire force and scientific fire strategy in the scene by using Ubiquitous technique to enormous disasters.

• Journal of Digital Contents Society
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• v.18 no.1
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• pp.225-229
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• 2017

In this paper, various units of industrial disaster safety threats as well as local and national facilities unit real-time detection and prevention refer to the corresponding system goes into disaster management preparedness, prevention, response recovery of phase I systematic ICT skills that can be managed more efficiently. In addition, the immediate disaster prevention and preparedness for early forecasting preemptive damage scale and high-tech information exchange technology to overcome the limitations of a human disaster in the field against the analysis and strategy of preemptive disaster safety management with smart risk management and prevention in response and recovery and the scene quickly and efficient mutual cooperation and effective collaboration and cooperation of the Community Center social security presented a smart disaster safety management system.

• Journal of the Korean housing association
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• v.6 no.2
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• pp.69-76
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• 1995

Recent opening of the era of local government and management randers study tasks concerning the improvement of the housing conditions by improving the problems in the residential conditions of the cheju Island region so as to help improve the life qualities of this legion make the area as an international resort place, and thus develop the indentify in the heat of the people in this region. The suggestions based on the study for the improvement of housing environment are summarized as follows: (1) To improve the collective housing. housing construction plan shall b made in harmony with the skylines of the Hanra mountain alongside the East-West rides across the long diameter of the oval shape of the Island, which includes 1) the construction of housing complex in harmony with and taking advantage of the natural scene of the area. and 2) the construction of variable housing readjustable in accordance with each family structure of variable housings for multi-families, which are believed not to provide quality housing conditions. Shall be entrained. (2) Encouraging the construction of detached house : 1) construction of housings in which three generations can reside together according to the traditional family structure in the region. 2) construction of the pastoral housings. 3) construction of tenement housings partitioned for each two families. 4) development of sliver town in the rural area. (3) Using the construction mateials produced in the Cheju I land will help promote the development of identity in the heart of the people in this region.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.1
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• pp.142-149
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• 2016

This paper proposes a method to detect LP(License Plate) of vehicles in indoor and outdoor parking lots. In restricted environment, there are many conventional methods for detecting LP. But, it is difficult to detect LP in natural and complex scenes with background clutters because several patterns similar with text or LP always exist in complicated backgrounds. To verify the performance of LP text detection in natural images, we apply MB-LGP feature by combining with ensemble machine learning algorithm in purpose of selecting optimal features of small number in huge pool. The feature selection is performed by adaptive boosting algorithm that shows great performance in minimum false positive detection ratio and in computing time when combined with cascade approach. MSER is used to provide initial text regions of vehicle LP. Throughout the experiment using real images, the proposed method functions robustly extracting LP in natural scene as well as the controlled environment.