• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.5 s.311
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• pp.1-9
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• 2006

Because most applications of vision-based object tracking demonstrate satisfactory operations only under very constrained environments that have simplifying assumptions or specific visual attributes, these approaches can't track target objects for the highly variable, unstructured, and dynamic environments like a traffic scene. An adaptive fusion framework is essential that takes advantage of the richness of visual information such as color, appearance shape and so on, especially at cluttered and dynamically changing scenes with partial occlusion[1]. This paper develops a particle filter based adaptive fusion framework and improves the robustness and adaptation of this framework by adding a new distinctive visual attribute, an image feature descriptor using SIFT (Scale Invariant Feature Transform)[2] and adding an automatic teaming scheme of the SIFT feature library according to viewpoint, illumination, and background change. The proposed algorithm is applied to track various traffic objects like vehicles, pedestrians, and bikes in a driver assistance system as an important component of the Intelligent Transportation System.

• Journal of the Korean Geographical Society
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• v.43 no.2
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• pp.220-234
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• 2008

In many security monitoring contexts, the performance or efficiency of surveillance sensors/networks based on a single sensor type may be limited by environmental conditions, like illumination change. It is well known that different modes of sensors can be complementary, compensating for failures or limitations of individual sensor types. From a location analysis and modeling perspective, a challenge is how to locate different modes of sensors to support security monitoring. A coverage-based optimization model is proposed as a way to simultaneously site k different sensor types. This model considers common coverage among different sensor types as well as overlapping coverage for individual sensor types. The developed model is used to site sensors in an urban area. Computational results show that common and overlapping coverage can be modeled simultaneously, and a rich set of solutions exists reflecting the tradeoff between common and overlapping coverage.

• Journal of Internet Computing and Services
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• v.21 no.3
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• pp.113-121
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• 2020

Human Pose Estimation (HPE) which localizes the human body joints becomes a high potential for high-level applications in the field of computer vision. The main challenges of HPE in real-time are occlusion, illumination change and diversity of pose appearance. The single RGB image is fed into HPE framework in order to reduce the computation cost by using depth-independent device such as a common camera, webcam, or phone cam. However, HPE based on the single RGB is not able to solve the above challenges due to inherent characteristics of color or texture. On the other hand, depth information which is fed into HPE framework and detects the human body parts in 3D coordinates can be usefully used to solve the above challenges. However, the depth information-based HPE requires the depth-dependent device which has space constraint and is cost consuming. Especially, the result of depth information-based HPE is less reliable due to the requirement of pose initialization and less stabilization of frame tracking. Therefore, this paper proposes a new method of HPE which is robust in estimating self-occlusion. There are many human parts which can be occluded by other body parts. However, this paper focuses only on head self-occlusion. The new method is a combination of the RGB image-based HPE framework and the depth information-based HPE framework. We evaluated the performance of the proposed method by COCO Object Keypoint Similarity library. By taking an advantage of RGB image-based HPE method and depth information-based HPE method, our HPE method based on RGB-D achieved the mAP of 0.903 and mAR of 0.938. It proved that our method outperforms the RGB-based HPE and the depth-based HPE.

• Journal of Digital Contents Society
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• v.7 no.4
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• pp.287-294
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• 2006

Mass-customization is fast growing a segment of the apparel market. 2D Virtual wearing system is one of visual support tools that make possible to sell apparel before producing and reduce the time and costs related to product development and manufacturing in the world of apparel mass-customization. This paper is related to fabric color mapping method for 2D image-based virtual wearing system. In proposed method, clothing shape section of interest is segmented from a clothes model image using a region growing method, and then mapping a new fabric color selected by user into it based on its intensity difference map is processed. With the proposed method in 2D virtual wearing system, regardless of color or intensity of model clothes, it is possible to virtually change the fabric color with holding the illumination and shading properties of the selected clothing shape section, and also to quickly and easily simulate, compare, and select multiple fabric color combinations for individual styles or entire outfits.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.3C
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• pp.92-101
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• 2005

It is difficult to detect the accurate detection which leads the camera it moves follows in change of the noise or illumination and Also, it could be recognized with backgound if the object doesn't move during hours. In this paper, the proposed method is updating changed background image as much as N＊M pixel mask as time goes on after get a difference between imput image and first background image. And checking image pixel can efficiently detect moving by computing fixed distance pixel instead of operate all pixel. Also, set up minimum area of object to use boundary point of object abstracted through checking image pixel and motion detect of object. Therefore motion detection is available as is fast and correct without doing checking image pixel every Dame. From experiment, the designed and implemented system showed high precision ratio in performance assessment more than 90 percents.

• Journal of Korea Multimedia Society
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• v.16 no.12
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• pp.1357-1367
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• 2013

Recently, as one of images based methods in facial expression recognition, the research which used ULBP block histogram feature and SVM classifier was performed. Due to the properties of LBP introduced by Ojala, such as highly distinction capability, durability to the illumination changes and simple operation, LBP is widely used in the field of image recognition. In this paper, we combined $LBP_{8,2}$ and $LBP_{8,1}$ to describe micro features in addition to shift, size change in calculating ULBP block histogram. From sub-windows of 660 of $LBP_{8,1}$ and 550 of $LBP_{8,2}$, ULBP histogram feature of 1210 were extracted and weak classifiers of 50 were generated using AdaBoost. By using the combined $LBP_{8,1}$ and $LBP_{8,2}$ hybrid type of ULBP histogram feature and SVM classifier, facial expression recognition rate could be improved and it was confirmed through various experiments. Facial expression recognition rate of 96.3% by hybrid boosted ULBP block histogram showed the superiority of the proposed method.

• International Journal of Highway Engineering
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• v.13 no.4
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• pp.151-158
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• 2011

Tunnel sections on the expressway are different from rest of sections on the expressway in terms of velocity, the number of passing cars, and vehicle density which, in particular, affect drivers' behavior before and after drivers pass through the tunnel. However, literature review reveals that former studies are too focused on quantitative indicator to consider qualitative aspects. Thus, this study tried to find out qualitative factors affecting speed reduction in tunnel sections based on questionnaire surveys and its analysis in tunnel sections selected by taking consideration of diverse conditions. Analysis showed that factors concerning tunnel configuration (lane width, shoulder width, and tunnel length) related to very long tunnels increasingly popular recently had some effects on reduced speed inside of tunnels. It appeared that visual environment such as visibility of tunnel entrance had an impact in speed reduction and vehicle speed tended to change according to lighting illumination level inside of tunnels. It is expected that continual investment would be made in technological development related to expressway tunnel design and service improvement based on this study.

• Journal of Digital Convergence
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• v.11 no.4
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• pp.229-234
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• 2013

The purpose of this study is to develop a lighting apparatus of the illuminance and color temperature to maximize the ability of the optimal combination of light sources that can be controlled efficiently control device. Finding people comfortable feeling for indoor lighting that can be used in a variety of color temperature illumination area by combining light sensitivity can be realized. Lighting apparatus for fluorescent lamps with different color temperature of 2000K and 8000K, and by varying the quantity of each of the fluorescent lamps, the illuminance of lighting equipment and color temperature through optical simulations were evaluated. By infrared remote control receiver, divided into 5 types of relaxation, conversation, meeting, hospitality, arts and the lighting environment you want to transfer the PC0 ~ PC4 through the parallel port on the mode selected by the user at the receiving end the DC voltage output. EEFL inverter input DC voltage and the DC input voltage, depending on the level of EEFL dimming value (illuminance and color temperature) lighting environment you want to create change while using a PIR sensor EEFL automatically turn off if people do not have was developed so that the power consumption so you can save.

• KIEAE Journal
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• v.13 no.5
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• pp.59-66
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• 2013

Current Architectural Facade Designs have been trending to increased glass areas resulting in increasing impact on interior lighting and daylighting. In regards to indoor environmental quality, the increase in window space has a large impact on the daylighting received which ultimately impacts the liveability of a space. Especially when considering seasons, in the summer, excessive daylighting can result in glare as well as put an increased load in conditioning the air space further reducing energy efficiency. As a result, in order to improve the sustainability performance of a building, it is important to limit the natural lighting exposure to properly meet the needs and conditions of the building occupants. One of the most representative features to limit excessive sunlight exposure, is to incorporate operable blind systems. To this end, this research has been based on simulations performance through the Radiance Program. Radiance is capable of analyzing performance of daylight and impact of sunlight. Through analysis of different slat angles and blind shapes, impact and minimization of energy usage was evaluated. Furthermore, seasonal analysis was performed in order to understand the effects of seasonal climate factors. Ultimately this research provides an analysis of operable blinds optimization and effects of blind shape, control factors and angle of shading.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.48 no.4
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• pp.6-13
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• 2011

Due to its robustness to illumination change, normalized cross-correlation based similarity measurement is widely used in many machine vision applications. However, its inefficient computation structure is not adequate for real-time embedded vision system. In this paper, we present an efficient hardware architecture based on a normalized cross correlation (NCC) for fast image similarity measure. The proposed architecture simplifies window-sum process of the NCC using the integral-image. Relieving the overhead to constructing integral image, we make it possible to process integral image construction at the same time that pixel sequences are inputted. Also the proposed segmented integral image method can reduce the buffer size for storing integral image data.