• Journal of Korea Society of Industrial Information Systems
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• v.28 no.6
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• pp.45-52
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• 2023

Recently, as the importance of walking in daily life has been emphasized, projects to guarantee walking rights and create a pedestrian environment are being promoted throughout the region. In previous studies, a pedestrian environment assessment was conducted using Jeonju-si road images, and an image comparison pair data set was constructed. However, data sets expressed in numbers have difficulty in generalizing the judgment criteria of pedestrian environment assessors or visually identifying the pedestrian environment preferred by pedestrians. Therefore, this study proposes a method to interpret the results of the pedestrian environment assessment through data visualization by building a web application. According to the semantic segmentation result of analyzing the walking environment components that affect pedestrian environment assessors, it was confirmed that pedestrians did not prefer environments with a lot of "earth" and "grass," and preferred environments with "signboards" and "sidewalks." The proposed study is expected to identify and analyze the results randomly selected by participants in the future pedestrian environment evaluation, and believed that more improved accuracy can be obtained by pre-processing the data purification process.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.83-89
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• 2021

In this paper, we propose an algorithm that provide services to consumers who want to conduct business by scientifically and systematically analyzing the number of pedestrians in a specific area over a specific period of time. In this paper, we proposed the algorithm to analyze the commercial area using the pedestrian-detect algorithm in the particular region using YOLO, one of the deep learning techniques. And with one image per minute in the images, the number of pedestrians is identified and this information is used for the analysis of business district on interesting area and time, systematically and objectively.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.07a
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• pp.411-412
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• 2012

본 논문에서는 인간의 가장 기본적이며 기초적인 운동인 걸음걸이로부터 검출할 수 있는 걸음 수 및 보행분석을 위해 전도성 섬유를 이용한 전기용량성압력 센서를 깔창형태로 개발하였다. 개발된 깔창 형태의 센서는 보행시의 압력을 측정하여 보행신호를 검출하고, 검출된 신호를 이용하여 걸음 수 및 보행 분석을 실시하였다. 개발된 센서의 성능 검증을 위하여 상용 만보계 및 관찰자의 수계로 도출된 보수를 비교하였으며, 자세에 따른 압력차이를 측정하였다. 기존의 상용 만보계는 저속(1 Km/h)으로 걸었을 때 보수가 잘 측정되지 않은 반면 개발된 센서는 저속에서도 관찰자 수계대비 정확한 보수를 도출 할 수 있었다. 또한 자세에 따라 압력 값을 토대로 사용자의 자세를 모니터링 할 수 있음을 보였다. 본 연구는 향후 스마트폰과 무선 연동하는 스마트 보행관리 시스템을 개발하기 위한 기초연구이다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.113-116
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• 2007

본 논문은 인간의 보행에 대한 에너지 분석을 통해 biped robot의 설계 단계에서 최적의 보행제어인자를 추출하기 위한 연구이다. 에너지 효율이 높은 보행인자 값을 얻기 위해 인간의 보행영상을 획득하고, 획득된 영상을 5-link biped robot model로 근사화하여 dynamics와 energy를 분석한다. 또한 link의 길이 비율과 link의 무게, link의 관성의 변화를 통해 5-link로 근사화된 인간의 보행 효율과 기구적 요소 사이의 민감도를 판단할 수 있다. 인간과 자유도가 다른 biped robot이 인간과 같은 보행을 위하여 설계단계에서 고려되어야할 중요한 기구적 요소가 이러한 민감도를 통해 구해진다.

• Journal of Korean Society of Transportation
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• v.32 no.6
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• pp.615-627
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• 2014

In this study, nonhierarchical K-mean cluster analysis is used to classify the types of 230 local governments and the Mann-Whitney U test and Kruskal-Wallis analysis are used to analyze the characteristics of pedestrian accidents by region types. With empirical analysis of pedestrian accidents, this study suggests improvements of walking environments reflecting local characteristics. Type 1-A (relatively dominant urban commercial areas), Type 1-B (predominantly urban residence) and Type 2 (rural areas) have been classified using nonhierarchical K-mean cluster analysis. According to the results, pedestrian accident rate on community roads was more than 60% for all types and incidence rate in rural areas was higher than that in urban areas. In addition, pedestrian accidents of Type 1-B have been found to occur more frequently than Type 2 in intersections and crossings, while the number of roadside casualties for Type 2 was highest.

• Smart Media Journal
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• v.1 no.2
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• pp.12-22
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• 2012

Today we are witnessing an increasingly widespread use of cameras in our lives for video surveillance, robot vision, and mobile phones. This has led to a renewed interest in computer vision in general and an on-going boom in human activity recognition in particular. Although not particularly fancy per se, human gait is inarguably the most common and frequent action. Early on this decade there has been a passing interest in human gait recognition, but it soon declined before we came up with a systematic analysis and understanding of walking motion. This paper presents a set of DBN-based models for the analysis of human gait in sequence of increasing complexity and modeling power. The discussion centers around HMM-based statistical methods capable of modeling the variability and incompleteness of input video signals. Finally a novel idea of extending the discrete state Markov chain with a continuous density function is proposed in order to better characterize the gait direction. The proposed modeling framework allows us to recognize pedestrian up to 91.67% and to elegantly decode out two independent gait components of direction and posture through a sequence of experiments.

• Journal of the KSME
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• v.50 no.12
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• pp.45-49
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• 2010

이 글에서는 기존의 운동학적(kinematics) 관점에서 주로 수행되어 오던 보행분석을 기계공학적으로 접근함으로써 보행특성에 대한 이해를 높인 사례들에 대해 소개하고자 한다.

• Journal of the KSME
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• v.50 no.12
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• pp.37-40
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• 2010

이 글에서는 보행분석을 위해 현재 많이 쓰이는 광학적모션캡처시스템 및 특수 보행분석을 위한 마커리스 모션캡처방법과 두 방향 엑스선영상 모션캡처방법에 대하여 소개한다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.53-61
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• 2022

Despite the increasing importance of pedestrians and their walking individualities, walking activity time characteristics are yet to be studied. This study analyzes the walking activity time characteristics by group using the Time Use Survey data. In order to analyze the characteristics of each pedestrian group, cluster analysis and correspondence analysis were performed by dividing the walking styles into utilitarian and leisure-purpose walking. Those who did not undertake utilitarian walking were mainly the worker group, whereas subjects who walked could be classified into homemaker and student groups. The peak of the student group appeared clearly in the morning, with a dispersed peak obtained during the afternoon. Although the peak of the homemaker group was not precise, it was confirmed that they mainly walked in the afternoon. The worker group also did not participate in leisure-purpose walking, while the elderly group mostly undertook walking for leisure. These walking activity time characteristics of pedestrians are expected to be applied when establishing related pedestrian policies.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.489-492
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• 2015

사용자의 위치기반 서비스에 대한 수요가 증가함에 따라 보행자의 현재 이동경로와 위치를 나타내는 '보행자 항법 시스템(PDR, Pedestrian Dead Reckoning)'에 관한 많은 연구들이 진행 중이다. 보행자 관성 항법 시스템은 IMU를 통해 데이터를 수신하여 각속도와 가속도 값을 구하고, 이 값을 토대로 사용자의 속도와 위치를 추정 한다. 또한 Zero-velocity(영속도)검출을 통해 누적되는 오차를 보정한다. 지금까지 대부분의 보행자 관성항법 시스템의 성능평가는 보행속도가 느리고 제한적인 상황에서 수행되었다. 하지만 이러한 상황은 보행자의 실제 보행상태를 반영하지 못한다. 본 논문에서는 다양한 보행속도에 따른 관성 항법 시스템의 성능을 실험하고 결과를 분석한다.