• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1001-1006
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• 2003

This paper presents the pedestrian navigation algorithm and the error compensation filter. The pedestrian navigation system (PNS) consists of the MEMS inertial sensors, the fluxgate, and the small-size GPS receiver. PNS calculates the navigational information using the signal patterns of the accelerometers. And the navigational information is completed by integration of the patterns, the fluxgate, and the GPS information. In general, PNS can provide the better solution than the low-cost inertial navigation system.

• Journal of information and communication convergence engineering
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• 제18권1호
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• pp.28-32
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• 2020

Railway transportation is the main land-based transportation in most countries. Accordingly, railway-transportation safety has always been a key issue for many researchers. Railway pedestrian accidents are the main reasons of railway-transportation casualties. In this study, we conduct experiments to determine which of the latest convolutional neural network models and algorithms are appropriate to build pedestrian railroad accident prevention systems. When a drone cruises over a pre-specified path and altitude, the real-time status around the rail is recorded, following which the image information is transmitted back to the server in time. Subsequently, the images are analyzed to determine whether pedestrians are present around the railroads, and a speed-deceleration order is immediately sent to the train driver, resulting in a reduction of the instances of pedestrian railroad accidents. This is the first part of an envisioned drone-based intelligent security system. This system can effectively address the problem of insufficient manual police force.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2018년도 추계학술발표대회
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• pp.808-810
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• 2018

Pedestrian tracking is a particular problem of object tracking, and an important component in various vision-based applications, such as autonomous cars or surveillance systems. After several years of development, pedestrian tracking in videos is still a challenging problem because of various visual properties of objects and surrounding environment. In this research, we propose a tracking-by-detection system for pedestrian tracking, which incorporates Convolutional Neural Network (CNN) and color information. Pedestrians in video frames are localized by a CNN, then detected pedestrians are assigned to their corresponding tracklets based on similarities in color distributions. The experimental results show that our system was able to overcome various difficulties to produce highly accurate tracking results.

• 한국ITS학회:학술대회논문집
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• 한국ITS학회 2007년도 제6회 추계학술대회 및 정기총회
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• pp.60-63
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• 2007

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권7호
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• pp.2321-2338
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• 2021

Compared with vehicle trajectories, pedestrian trajectories have stronger degrees of freedom and complexity, which poses a higher challenge to trajectory prediction tasks. This paper designs a mode to divide the trajectory of pedestrians at a traffic intersection, which converts the trajectory regression problem into a trajectory classification problem. This paper builds a deep model for pedestrian trajectory prediction at intersections for the task of pedestrian short-term trajectory prediction. The model calculates the spatial correlation and temporal dependence of the trajectory. More importantly, it captures the interactive features among pedestrians through the Attention mechanism. In order to improve the training speed, the model is composed of pure convolutional networks. This design overcomes the single-step calculation mode of the traditional recurrent neural network. The experiment uses Vulnerable Road Users trajectory dataset for related modeling and evaluation work. Compared with the existing models of pedestrian trajectory prediction, the model proposed in this paper has advantages in terms of evaluation indicators, training speed and the number of model parameters.

• 한국산학기술학회논문지
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• 제12권1호
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• pp.396-404
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• 2011

최근 GPS 기능을 내장한 스마트폰의 보급이 확대됨에 따라 위치를 기반으로 하는 다양한 응용 서비스들이 제공되고 있다. 기존의 보행자 길안내 서비스는 차량 길안내 서비스를 확장하여 경로 질의를 처리하고 있으나, 인도에 대한 적절한 경로 안내가 어려울 뿐 아니라 차량을 위한 도로 네트워크 저장구조는 관심지점 위주의 경로 질의 처리에 문제를 야기한다. 또한, 저장 장치의 입출력 빈도수를 증가시켜 스마트 폰의 전력 소모를 가중시키게 된다. 본 논문에서는 보행자 경로의 정확한 표현을 위해 보행자 도로 네트워크 모델을 정의하고 저장 장치의 입출력 빈도수를 줄이기 위한 관심지점 기반 보행자 도로 네트워크 저장 구조를 제안한다. 제안 기법은 보행자 도로의 특성과 요구사항에 따른 관심지점 기반의 정확한 경로 탐색을 지원한다. 또한, 관심지점을 고려한 데이터 구조를 제공하여 경로 탐색 질의 처리 비용을 감소시켜 스마트폰의 전력 소모를 줄일 수 있다.

• 한국실내디자인학회논문집
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• 제28호
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• pp.140-148
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• 2001

The purpose of this thesis is to provide basic information of efficient flow line arrangement, which results from examining the factors of route choice with a focus on the store' space elements and pedestrian activity patterns in the outlets. The route tracking is applied to grasp pedestrian activity patterns, therefore, a concrete analysis into influential factors of the space structure arrangement and forms on route choice. The route tracking is a means to understand pedestrian activity patterns by establishing an unrecognizable space and examining every route in the investigating area for pedestrian activity pattern research. Three sample stores have different systems in the ground plan structures, the escalator location and the directions. The analysis focuses on the booth arrangement and shopping patterns. In conclusion, route choice of the customers and the structure of the space are quite closely related and affect the quality of shopping. This can suggest evidence for the need of the space structure to meet the pedestrian activity patterns.

• Journal of Multimedia Information System
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• 제6권1호
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• pp.1-6
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• 2019

In the field of industrial applications, the real-time performance of the target detection problem is very important. The most serious time consumption in the pedestrian detection process is the extraction phase of the candidate window. To accelerate the speed, in this paper, a fast extraction of pedestrian candidate window based on the BING (Binarized Normed Gradients) algorithm replaces the traditional sliding window scanning. The BING features are extracted with the positive and negative samples and input into the two-stage SVM (Support Vector Machine) classifier for training. The obtained BING template may include a pedestrian candidate window. The trained template is loaded during detection, and the extracted candidate windows are input into the classifier. The experimental results show that the proposed method can extract fewer candidate window and has a higher recall rate with more rapid speed than the traditional sliding window detection method, so the method improves the detection speed while maintaining the detection accuracy. In addition, the real-time requirement is satisfied.

• Physical Therapy Rehabilitation Science
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• 제10권2호
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• pp.124-133
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• 2021

Objective: In order to secure the right to walk for the weak, such as the disabled, this study aims to suggest ways to improve the pedestrian environment by identifying factors that cause obstacles to walking. Design: Data Analysis and Perception Survey. Methods: The questionnaire was conducted separately between users of personal mobility vehicle and non-users. A total of 207 effective questionnaires were collected, and the analysis analyzed the perception of personal mobility vehicle by conducting frequency analysis using SAS 9.4. The survey focused on basic information on respondents, walking conditions, understanding of personal mobility vehicle, awareness of pedestrian space passage and parking, and awareness of the possibility of securing pedestrian rights due to new regulations. Results: First, when moving a pedestrian path by personal mobility vehicle, it shall be limited to less than the walking speed of pedestrians. Second, the parking location of the personal mobility vehicle is located at the boundary of the pedestrian road and the lane. Third, pay a fair price to park in a pedestrian space. Conclusions: It is necessary to improve the system to strengthen the contents of education to take into account the safety of pedestrians in education on how to use personal mobility vehicle.

• 한국콘텐츠학회논문지
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• 제19권10호
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• pp.179-189
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• 2019

한국의 교통 패러다임이 차량 중심에서 보행 중심의 사회로 변화하고 있다. 이러한 과정에서 보행자 안전 및 보행환경 개선의 관심 또한 증가하고 있는 추세이다. 하지만 한국의 교통안전 수준은 여전히 심각한 수준이다. 따라서 보행자 안전 및 보행환경을 개선하기 위한 노력이 절실한 상황이다. 이에 본 연구는 어린이 보호구역 내 안전한 보행환경을 조성하기 위해 교통사고분석시스템(TAAS)에서 제공하는 2013-2015년 차대사람 교통사고 데이터를 활용하여 어린이 보호구역 주변 근린환경과 보행자 교통사고와의 연관성을 지리정보시스템(GIS)와 공간계량분석을 통해 파악하였다. 주요 분석 결과는 다음과 같다. 첫째, 도로요인과 대중교통요인 모두 어린이 보호구역 내 보행자 교통사고에 부정적 영향을 미치는 것으로 나타났다. 둘째, 토지이용요인의 경우 주거지역, 상업지역, 공업지역 모두 보행자 교통사고에 부정적 영향을 미치는 것으로 나타났다. 한편, 용도혼합도의 경우에는 보행자 교통사고 저감에 긍정적 영향을 미치는 것으로 나타났다. 마지막으로, 개발밀도가 높은 경우에도 어린이 보호구역 내 보행자 교통사고에 부정적 영향을 미치는 것으로 나타났다.