• Journal of information and communication convergence engineering
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• v.13 no.3
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• pp.197-204
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• 2015

In this paper, we present an algorithm for the detection of illegally parked vehicles based on a combination of some image processing algorithms. A digital camera is fixed in the illegal parking region to capture the video frames. An adaptive Gaussian mixture model (GMM) is used for background subtraction in a complex environment to identify the regions of moving objects in our test video. Stationary objects are detected by using the pixel-level features in time sequences. A stationary vehicle is detected by using the local features of the object, and thus, information about illegally parked vehicles is successfully obtained. An automatic alarm system can be utilized according to the different regulations of different illegal parking regions. The results of this study obtained using a test video sequence of a real-time traffic scene show that the proposed method is effective.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5D
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• pp.485-496
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• 2010

An increase in number of vehicles owned by individuals worsens the conditions of parking in residential areas. So to speak, the pedestrians' safety is seriously threatened by illegally parked vehicles on the residential area roads. As a result, the number of vehicle-to-pedestrian accidents has been increasing annually. Also, illegal parking on arterial roads is increasingly becoming common, especially by cooommercial trucks. However, no solution has been found to reduce or eliminate accidents caused by vehicles illegally parked on readside. The result of this study provides the solutions to enhance the safety of residential area roads and arterial roads, from viewpoints of both long-term and short-term, by collecting data about the status of illegal parking and addressing critical problems.

• Smart Media Journal
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• v.1 no.3
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• pp.48-55
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• 2012

In general, background subtraction based methods are used to detect the moving objects in visual tracking applications. In this paper we employed background subtraction based scheme to detect the temporarily stationary objects. We proposed two schemes for stationary object detection and we compare those in terms of detection performance and computational complexity. In the first approach we used single background and in the second approach we used dual backgrounds, generated with different learning rates, in order to detect temporarily stopped object. Finally, we used normalized cross correlation (NCC) based image comparison to monitor and track the detected stationary object in a video scene. The proposed method is robust with partial occlusion, short time fully occlusion and illumination changes, as well as it can operate in real time.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.201-213
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• 2021

Recently, personal mobility has been spreading and using increasing, but the pedestrian environment is getting worse and accidents are also rapidly increasing. Therefore, this study conducts a status survey related to the elements of pedestrian disturbances in personal mobility and identifies the problems. The following measures are presented to improve the pedestrian environment for the mobility handicapped through expert opinion surveys. The movement of individual mobility means in the walking space is prohibited, and the speed limit shall be stipulated to enable the mobility handicapped to walk safely and conveniently. Parking spaces will have to create obstacle zones in the parking area next to the roadway or at the border of sidewalks and roads, and regulations are needed to collect illegally parked vehicles. It is necessary to switch from the existing automobile-oriented road to the road structure considering the use of low and medium-speed vehicles.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.4
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• pp.133-142
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• 2021

With the recent advancements of deep learning, companies such as smart home, healthcare, and intelligent transportation systems are utilizing its functionality to provide high-quality services for vehicle detection, emergency situation detection, and controlling energy consumption. To provide reliable services in such sensitive systems, deep learning models are required to have high accuracy. In order to develop a deep learning model for analyzing previously mentioned services, developers should utilize the state of the art deep learning models that have already been verified for higher accuracy. The developers can verify the accuracy of the referenced model by validating the model on the dataset. For this validation, the developer needs structural information to document and apply deep learning models, including metadata such as learning dataset, network architecture, and development environments. In this paper, we propose a description language that represents the network architecture of the deep learning model along with its metadata that are necessary to develop a deep learning model. Through the proposed description language, developers can easily verify the accuracy of the referenced deep learning model. Our experiments demonstrate the application scenario of a deep learning description document that focuses on the license plate recognition for the detection of illegally parked vehicles.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.251-265
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• 2023

The purpose of this study is to deduce key indicators in evaluating the pedestrian environment for the elderly in Busan, which has entered an aging society, and to propose policy improvement measures. The key indicators were selected based on prior research and surveys, and the effectiveness of those indicators were measured through evaluations conducted on three places which have the highest proportion of the elderly population in Busan. The summaries of analysis are as follow. First, the three places are hillslide residential areas, and areas of activity that the elderly have were very narrow due to the restrictions on their movement caused by slope. Second, the areas were filled with a number of illegally parked vehicles. And the degree of segregation of pedestrian and vehicle and the level of safety were very low. Third, the streets with steep slopes of the target site force the elderly to move vertically, and for this reason, the elderly are expressing difficulties in outdoor activities. Fourth, it was found that the target site lacked a space for relaxation during outdoor activities. The poor walking environment not only limit the essential and social activities of the elderly, but also adversely affects the health and quality of life of the elderly. In order to maintain the health of the elderly and improve the quality of life, actions should be taken to improve the walking factors that affect the movement and external activities of the elderly.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.549-559
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• 2014

The rapid expansion of cities led to the shortage of housing in urban areas. The government compensated for this shortage through large scale residential developments that increased the housing supply. The supply of condominium apartments remains above 83% of the entire housing supply, and the proportion of apartments are at a steady increase, at about 50%. Due to the increase, illegally parked cars resulting from the shortage of parking spaces within the apartment complex have become increasingly problematic as they block the transit of emergency vehicles, and heighten the tension among neighboring residents in obtaining a parking space. Especially, the future residents are considered to plan the parking based on the estimated demand for parking. However, the parking unit method utilized to estimate the parking demand accounts for the exclusive use of space, which is believed to be far from the parking demands in reality. The reason for this discrepancy is that, as the number of households decrease, and area of exclusive space is expanded, the planned parking increases. On the other hand, when the number of households increase, and the area of exclusive space is reduced, the planned parking decreases, thus methods to recalculate the parking units based on estimated parking demand is an urgent concern. To estimate the parking units based on condominium apartments, this study first examined the existing research literature, and appointed the field of investigation to collect the necessary data. In addition, field study data and surveys collected and analyzed, in order to identify the problems underlying parking units, and problems regarding the current traffic impact assessment parking unit calculation method were deduced. Through identifying the influential factors on parking demand estimates, and performing a factorial analysis based on the collected data, the variables were selected in relation to the parking demand estimates, to develop the parking unit estimate model. Finally, through comparing and verifying the existing traffic impact assessment parking unit estimate against the newly developed model using collected data, a far more realistic parking unite estimate was suggested, reflecting the characteristics of the residents. The parking unit estimate model developed in this study is anticipated to serve as the guidelines for future parking lot legislature, as wel as the basis to provide a more realistic estimate of parking demands based on the resident characteristics of an apartment complex.