• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2004.11a
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• pp.233-238
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• 2004

This study extracted and analyzed physical components of street view with external streets at large-scaled apartment house complex of Sangmu Housing Site Development District in Gwangju, examined factors affecting the image of street view and visual perceptional characteristics by image, analyzed relationship between components of street view and visual preferences of image and aimed to provide basic materials needed for making external street view at apartment house complex of high Qualify.

• Journal of the Korean housing association
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• v.17 no.3
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• pp.123-131
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• 2006

This study examined types and color conditions of street views through relationship of high-storied apartment house to street components which has great visual influence on urban street view and requires harmony with street environment as background factor and conducted positive experiment with high-storied apartment houses located at housing site development districts in Gwangju Metropolitan City since 1990s in order to set applicable color ranges in designing external colors of high-storied apartment houses which became background of street view by types. Consequently, in image changes of four factors of main colors in classified street types, P, RP, R and YR colors showed high average values in naturalness, harmony and unity and GY, G, BG and B colors showed dichotomy with low average value, but image of personality showed generally low average value. RP, R and YR colors showed higher adaptability and GY, G and BG colors showed lower adaptability. It was confirmed that according to adaptability of main colors used in high-storied apartment houses by street types, there was difference of appropriate color range in street components and external colors of high-storied apartment houses by street types.

• ETRI Journal
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• v.39 no.1
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• pp.97-107
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• 2017

A fast and accurate building-level visual place recognition method built on an image-retrieval scheme using street-view images is proposed. Reference images generated from street-view images usually depict multiple buildings and confusing regions, such as roads, sky, and vehicles, which degrades retrieval accuracy and causes matching ambiguity. The proposed practical database refinement method uses informative reference image and keypoint selection. For database refinement, the method uses a spatial layout of the buildings in the reference image, specifically a building-identification mask image, which is obtained from a prebuilt three-dimensional model of the site. A global-positioning-system-aware retrieval structure is incorporated in it. To evaluate the method, we constructed a dataset over an area of $0.26km^2$. It was comprised of 38,700 reference images and corresponding building-identification mask images. The proposed method removed 25% of the database images using informative reference image selection. It achieved 85.6% recall of the top five candidates in 1.25 s of full processing. The method thus achieved high accuracy at a low computational complexity.

• KIEAE Journal
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• v.7 no.4
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• pp.31-38
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• 2007

Streetscape plays on important role in urban cities. Characteristics of streets is basically defined by the building facade, signs, plants and paving during the daytime. However at night, street receives a new appearance due to the shop light from the buildings, exterior lightings, signboards and street light, and it creates most of the image of the streets. This study aims to analyze the luminous environment and its subjective image of two different pedestrian's commercial streets. Insa-dong street and Myungdong street were chosen for the study. Horizontal illuminance and luminance on building surface, advertisement billboards and pedestrian road were measured. Thirty students were asked to rate the five scaled questionnaire on their subjective images of the streets. Statistical analysis including profile, correlation and T-test are conducted and some findings are discussed

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.888-896
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• 2018

In this paper, we report detection and recognition of vehicle logo from images captured from street CCTV. Image data includes both the front and rear view of the vehicles. The proposed method is a two-step process which combines image preprocessing and faster region-based convolutional neural network (R-CNN) for logo recognition. Without preprocessing, faster R-CNN accuracy is high only if the image quality is good. The proposed system is focusing on street CCTV camera where image quality is different from a front facing camera. Using perspective transformation the top view images are transformed into front view images. In this system, the detection and accuracy are much higher as compared to the existing algorithm. As a result of the experiment, on day data the detection and recognition rate is improved by 2% and night data, detection rate improved by 14%.

• Archives of design research
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• v.17 no.2
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• pp.135-146
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• 2004

The street landscape image is through complex experience of psychological factor by the visionary experience and physical factor by recognize a street's structure. Therefore, the need for analyz-ing and evaluating the psychological and physical aspect of street view was aroused, and how much it has an effect on the outcome. Above all, a definite street standard of a region in its characteristics was selected to analyze the street characteristics of a region (commercial, business, and complex area). A questionnaire was used to measure psychological information felt in a street area. As a result, the street image holds similar characteristics according to regional characteristics and the amenity and busy condition play a major role in having the effect. To know of the effect of street of a region that is known to cause the busy in a region, the discriminant analysis was made between the selected regions to analyze the difference. As a result, the difference of the width of street, ratio of widths of sidewalk and driveway, the ratio of height of a building and width of street, and the difference of tree-planting ratio were main factors which helped to feel more of the contrary of street in a region. Current research has helped to make more precise analysis and evaluation of all kinds of street images, and suggested different means of having more live image in a street region through physical factors. To create more the busy in a region, it is considered that analyzing the image of a street would be used more.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.331-341
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• 2019

With the popularity of sensor-rich environments, smartphones have become one of the major platforms for obtaining and sharing information. Since it is difficult to utilize GNSS (Global Navigation Satellite System) inside the area with many buildings, the localization of smartphone in this case is considered as a challenging task. To resolve problem of localization using smartphone a four step image-based localization method and procedure is proposed. To improve the localization accuracy of smartphone datasets, MMS (Mobile Mapping System) and Google Street View were utilized. In our approach first, the searching for candidate matching image is performed by the query image of smartphone's using GNSS observation. Second, the SURF (Speed-Up Robust Features) image matching between the smartphone image and reference dataset is done and the wrong matching points are eliminated. Third, the geometric transformation is performed using the matching points with 2D affine transformation. Finally, the smartphone location and attitude estimation are done by PnP (Perspective-n-Point) algorithm. The location of smartphone GNSS observation is improved from the original 10.204m to a mean error of 3.575m. The attitude estimation is lower than 25 degrees from the 92.4% of the adjsuted images with an average of 5.1973 degrees.

• Journal of Digital Contents Society
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• v.19 no.4
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• pp.605-613
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• 2018

In this paper, we propose a system to walk around the world with virtual reality technology. Although the virtual reality users are interested in the virtual travel contents, the conventional virtual travel contents have limited space for experiencing and lack of interactivity. In order to solve the problem of lack of realism and limited space, which is a disadvantage of existing contents, this system created a virtual space using Google Street View image. Users can have realistic experience with real street images, and travel a vast area of the world provided by Google Street View image. Also, a virtual reality headset and a treadmill equipment are used so that the user can actually walk in the virtual space, which maxmizes user interactivity and immersion. We expect this system contributes to the leisure activities of virtual reality users by allowing natural walking trip from famous tourist spots to even mountain roads and alleys.

• Journal of information and communication convergence engineering
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• v.10 no.4
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• pp.411-419
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• 2012

This paper proposes a semi-automatic image-based approach for 3-dimensional (3D) modeling of buildings along streets. Image-based urban 3D modeling techniques are typically based on the use of aerial and ground-level images. The aerial image of the relevant area is extracted from publically available sources in Google Maps by stitching together different patches of the map. Panoramic images are common for ground-level recording because they have advantages for 3D modeling. A panoramic video recorder is used in the proposed approach for recording sequences of ground-level spherical panoramic images. The proposed approach has two advantages. First, detected camera trajectories are more accurate and stable (compared to methods using multi-view planar images only) due to the use of spherical panoramic images. Second, we extract the texture of a facade of a building from a single panoramic image. Thus, there is no need to deal with color blending problems that typically occur when using overlapping textures.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.16-27
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• 2010

A street, as a linear factor constituting the city, is an axis of urban development. The substantial function of the street is the traffic space for the passage but now it plays the important role of the place of community where contains various activities such as meeting between people and people, rest, entertainment etc. A street is basically the 3 dimensional space consisted of the sidewalk, roadway and the roadside structures surrounding the street. In this case, the roadside structures are the physical composition factors for the street space and the facade of the roadside structures acts as important variables to form the image of street space. Thus, this study is to provide the basic data to be applied in the future urban street landscape plan by extracting the superior factors in visual and perceptional aspects which affect the image of street view from the shape composition factors which constitute the facade of the roadside structures, and by searching and analyzing the satisfaction degree and preference of each factors.