• Journal of the Korean housing association
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• v.20 no.2
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• pp.87-99
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• 2009

The brand is getting more important purchase factor in apartment market, so domestic construction companies have tried to differentiate it from others by creating the unique brand image. The purpose of this study was to investigate consistency of apartment brand image as a process which includes publicity, design and customer service and to analyze how using intergrated brand image affects brand preference and purchasing intention. To examine hypotheses, an empirical study using a survey questionnaire for residents living in 4 different brand apartments in Dongtan, Hwasung city was conducted. The collected data were treated with the SPSS Win Program 14.0. The study indicates that residents living in brand apartment generally preferred natural friendly image, high-class image and modern image to the others. And at first apartment brand images were created with image advertising on TV, catalog for sale and model house tour, but residents have most needs for customer service reflected in brand images. The study also has found that brand images in each process including publicity, design and customer service were not intergrated. However brand image intergration had positive effects on residential satisfaction and customer loyalty. The results of the study are expected to become the useful data in developing sustainable apartment brands and building effective marketing strategy of construction companies.

• Journal of Korea Multimedia Society
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• v.5 no.2
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• pp.167-175
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• 2002

Image Mosaicing creates a new image by composing video frames or still images that are related, and performed by arrangement, composition and redundancy analysis of images. This paper proposes a hierarchical image mosaicing system using camera and object parameters far efficient video database construction. A tree-based image mosiacing has implemented for high-speed computation time and for construction of static and dynamic image mosaic. Camera parameters are measured by using least sum of squared difference and affine model. Dynamic object detection algorithm has proposed for extracting dynamic objects. For object extraction, difference image, macro block, region splitting and 4-split detection methods are proposed and used. Also, a dynamic positioning method is used for presenting dynamic objects and a blurring method is used for creating flexible mosaic image.

• Journal of KIBIM
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• v.6 no.2
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• pp.39-46
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• 2016

While institutional matters such as improvement on Basic Guidelines for Construction Safety are greatly concerned to reduce falling accidents at construction sites, there are short of studies on how to practically predict accident signs at construction sites and to preemptively prevent them. As one of existing accident prevention methods, it was attempted to build the early warning system based on standardized accident scenarios to control the situations. However, the investment cost was too high depending on the site situation, and it did not help construction workers directly since it was developed to mainly provide support operational work support to safety managers. In the long run, it would be possible to develop the augmented reality based accident prevention method from the worker perspective by extracting product information from BIM, visually rendering it along with site installation materials term and comparing it with the site situation. However, to make this method effective, the BIM model should be implemented first and the technology that can promptly process site situations should be introduced. Accordingly, it is necessary to identify risk signs through lightweight image processing to promptly respond only with currently available resources. In this study, it was intended to propose the system concept that identified potential risk factors of falling accidents by histogram equalization, which was known as the fastest image processing method presently, used visual words, which could enhance model classification by wording image records, to determine the risk factors and notified them to the work manager.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.221-222
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• 2021

Conventionally, in material management at a construction site, the type, size, and quantity of materials are identified by the eyes of the worker. Labor-intensive material management by manpower is slow, requires a lot of manpower, is prone to errors, and has limitations in that computerization of information on the identified types and quantities is additionally required. Therefore, a method that can quickly and accurately determine the type, size, and quantity of materials with a minimum number of workers is required to reduce labor costs at the construction site and improve work efficiency. In this study, we developed an automated convolution neural network(CNN) and computer vision technology-based rebar size and quantity estimation system that can quickly and accurately determine the type, size, and quantity of materials through images.

• Journal of the Korea Institute of Building Construction
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• v.16 no.5
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• pp.471-477
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• 2016

The construction industry is very important to supply the facilities and infrastructure in Korea. However, the images of construction industry are negative in actual. In addition, the studies to improve the images of construction industry up to now have a limitation to research the images about that time. So, in this study, the authors examined and analyzed the peoples' trend changes of the images of construction industry with time. The results showed that the positive images of construction industry about the contribution to national economy and the future prospect are diminished. And it is revealed that the negative images of construction industry about the morality are decreased, too. The authors proposed the strategies to improve the images of construction industry by the based on these results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.6
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• pp.1524-1529
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• 2007

In this paper, automatic shot panorama construction method is presented. For construction of panorama image, conventional panoramic techniques manually took two panorama members, but the proposed method automatically takes panorama members according to moving camera and constructs panorama image. The panorama members are automatically selected and taken by tracking region over image stream form camera. Matching region for panorama including the tracking region in the members is selected and applied by invariant feature panoramic method. Our method can automatically shot panorama members and has merit of high processing speed. In the experiments, it was shown that the algorithm required about 0.89 second in processing time, about two times shorter than existing invariant feature based one(6), for color images of $320{\times}240$ size.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.3
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• pp.399-407
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• 2019

In Korea, the construction industry has been known to have the highest risk of safety accidents compared to other industries. Therefore, in order to improve safety in the construction industry, several researches have been carried out from the past. This study aims at improving safety of labors in construction site by constructing an effective automatic safety helmet detection system using object detection algorithm based on image data of construction field. Deep learning was conducted using Region-based Fully Convolutional Network (R-FCN) which is one of the object detection algorithms based on Convolutional Neural Network (CNN) with Transfer Learning technique. Learning was conducted with 1089 images including human and safety helmet collected from ImageNet and the mean Average Precision (mAP) of the human and the safety helmet was measured as 0.86 and 0.83, respectively.

• Korean Journal of Construction Engineering and Management
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• v.23 no.2
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• pp.45-53
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• 2022

The purpose of this study is to present a model for analyzing construction errors of reinforced concrete pile foundations using drones. First, a drone is used to obtain an aerial image of the construction site, and an orthomosaic image is generated based on those images. Then, the circular pile foundation is automatically recognized from the orthomosaic image by using the Hough transform circle detection method. Finally, the distance is calculated based on the the center point of the reinforced concrete pile foundation in the overlapped data. As a case study, the proposed concrete concrete pile foundation construction quality control model was applied to the real construction site in Incheon to evaluate the proposed model.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.2 s.20
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• pp.49-56
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• 2002

Many users of 3D virtual city are Utilize a texture image for the cognition of real object. In this study, building's facet images were achieved by a digital camera and adjusted its distortion by use of the 2D projective transformation method. After then, Images are mapped to a 3D building model by means of the OpenGL. Application program is able to offer an automation solution to construction process of the 3D virtual city.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2008.11a
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• pp.357-362
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• 2008

The brand is getting more important purchase factor in apartment market, so domestic construction companies have tried to differentiate it from others using the unique brand image. The purpose of this study is to investigate consistency brand images as a process which includes publicity, design and customer service and to analyze how using intergrated brand image affects brand preference and purchasing intention. To examine hypotheses, empirical study survey questionnaire for consumers who reside in 4 different brand apartments in Dongtan, Hwasung city is conducted. The results of the study are expected to become the useful data in developing sustainable apartment brand and building the marketing strategy of construction companies.