• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.9
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• pp.1035-1042
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• 2014

Object recognition is one of the key technologies of the monitoring system for the prevention of various intelligent crimes. The height is one of the physical information of a person, and it may be important information for identification of the person. In this paper, a method which can detect pedestrians from CCTV images and estimate the height of the detected objects, is proposed. In this method, GMM (Gaussian Mixture Model) method was used to separate the moving object from the background and the pedestrian was detected using the conditions such as the width-height ratio and the size of the candidate objects. The proposed method was applied to the CCTV video, and the height of the pedestrian at far-distance, middle- distance, near-distance was estimated for the same person, and the accuracy was evaluated. Experimental results showed that the proposed method can estimate the height of the pedestrian as the accuracy of 97% for the short-range, 98% for the medium-range, and more than 97% for the far-range. The image sizes for the same pedestrian are different as the position of him in the image, it is shown that the proposed algorithm can estimate the height of pedestrian for various position effectively.

• The KIPS Transactions:PartA
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• v.19A no.4
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• pp.175-180
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• 2012

This paper describes the design of high-performance pedestrian and vehicle detection circuit using the Haar-like features. The proposed circuit uses a sliding window for every image frame in order to extract Haar-like features and to detect pedestrians and vehicles. A total of 200 Haar-like features per sliding window is extracted from Haar-like feature extraction circuit and the extracted features are provided to AdaBoost classifier circuit. In order to increase the processing speed, the proposed circuit adopts the parallel architecture and it can process two sliding windows at the same time. We described the proposed high-performance pedestrian and vehicle detection circuit using Verilog HDL and synthesized the gate-level circuit using the 130nm standard cell library. The synthesized circuit consists of 1,388,260 gates and its maximum operating frequency is 203MHz. Since the proposed circuit processes about 47.8 $640{\times}480$ image frames per second, it can be used to provide the real-time detection of pedestrians and vehicles.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.61-68
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• 2022

In this paper, we propose a system to predict the GPS trajectory of a pedestrian based on a deep learning model. Pedestrian trajectory prediction is a study that can prevent pedestrian danger and collision situations through notifications, and has an impact on business such as various marketing. In addition, it can be used not only for pedestrians but also for path prediction of unmanned transportation, which is receiving a lot of spotlight. Among various trajectory prediction methods, this paper is a study of trajectory prediction using GPS data. It is a deep learning model-based study that predicts the next route by learning the GPS trajectory of pedestrians, which is time series data. In this paper, we presented a data set construction method that allows the deep learning model to learn the GPS route of pedestrians, and proposes a trajectory prediction deep learning model that does not have large restrictions on the prediction range. The parameters suitable for the trajectory prediction deep learning model of this study are presented, and the model's test performance are presented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.219-221
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• 2022

In recent summer, as it is concentrated, even in mountainous areas, flooding and flooding cause casualties in pedestrian evacuation situations. To compensate for this, a system that detects the occurrence of flooding and allows pedestrians to evacuate safely is required. Therefore, in this paper, we propose a research on pedestrian path search based on the shortest distance algorithm using Map API. The pedestrian route search system outputs a map using the T Map API, selects nearby buildings as shelters, and stores data. A shelter close to the pedestrian's current location is selected, and the shortest route is output and the distance and time are provided. If there is a problem with the current route during evacuation, another shelter route is provided from the current location. Therefore, it is thought that the pedestrian route search evacuation system proposed in this paper will prevent accidents during evacuation.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.09a
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• pp.372-375
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• 2010

보안등은 주택가 골목에 안전을 위해 설치하는 중요한 설비로서, 도로 폭이 12m 이하인 장소에 설치된다. 그러내 통행 인구가 없어도 야간시간 내내 점등되고 있기에 낭비되는 전력량이 상당하다. 적외선센서가 부착된 보안등을 교체하게 되면 보행자의 움직임을 통해 일정시간 점등이 되고 이동체가 없을 때는 소등이 되어 전기에너지의 소비를 상당히 줄일 수가 있어 온실가스저감에 기여할 수 있다. 본 논문에서는 적외선센서 보안등의 최적 작동시간을 추적하기 위해 보행자의 통행 분포를 알아보고자 연구지역인 경북대 캠퍼스 내에서 사계절 중 여름철 야간 보행자의 통행패턴을 현장조사하여 분석하였다. 이를 통해 시간별, 공간별 분포 특성을 파악하고 도식화하여 보행자의 통행분포 특성을 파악함으로써 보안등의 작동시간 추적이 가능하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.931-934
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• 2016

본 논문에서는 횡단보도의 보행자와 차량 간에 효율적인 도로 사용을 유지하면서 횡단보도 사고의 많은 부분을 차지하는 야간 횡단보도 보행자 사고를 센서, 카메라, 투광기 및 네트워크를 활용하여 사전예방하고 사고 발생 시 이를 적극적으로 추적하고 후속 조치를 취할 수 있는 시스템을 제안한다. 제안하는 시스템은 보행자가 횡단보도에 진입하였을 때 보행자에게 조명을 비추어 보다 먼 거리에서 운전자가 용이하게 식별을 할 수 있으며, 횡단보도 내 사고 발생 시 관제 센터에서 현장 정보를 수신 받아 상황에 맞춰 대응할 수 있는 환경을 제공한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.5
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• pp.1080-1088
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• 2004

In this paper, the interesting moving objects tracking algorithm using color information on Multi-Video camera against variance of intensity, shape and background is proposed. Moving objects are detected by using difference image method and integral projection method to background image and objects image only with hue area, after converting RGB color coordination of image which is input from multi-video camera into HSI color coordination. Hue information of the detected moving area are segmented to 24 levels from $0^{\circ}$ to $360^{\circ}$. It is used to the feature parameter of the moving objects that are three segmented hue levels with the highest distribution and difference among three segmented hue levels. To examine propriety of the proposed method, human images with variance of intensity and shape and human images with variance of intensity, shape and background are targeted for moving objects. As surveillance results of the interesting human, hue distribution level variation of the detected interesting human at each camera is under 2 level, and it is confirmed that the interesting human is tracked and surveilled by using feature parameters at cameras, automatically.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.921-923
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• 2014

보행자 검출과정은 특징추출, 추출된 특징을 기반으로 한 학습과정, 그리고 학습된 데이터를 기반으로 한 분류과정으로 나눌 수 있다. 이들 중 연산시간이 가장 오래 걸리는 특징추출과정이다. 기존의 HOG 특징 추출은 하나의 학습 샘플 이미지에 대하여 많은 픽셀 연산이 필요하기 때문에 많은 시간이 소요되었다. 본 논문에서는 실시간 스트리밍 환경에서 이전 프레임의 HOG 특징 검출정보를 분석하여 다음 프레임에서 보행자가 존재 할 가능성이 높은 부분에 대해서만 특징을 추출한다. 이 방법으로 기존의 연구와 비교하여 인식성능에는 거의 영향을 주지 않고 인식 속도를 향상할 수 있다.

• The Journal of the Korea Contents Association
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• v.19 no.10
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• pp.179-189
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• 2019

Korea's transportation paradigm is shifting from a vehicle-centered to a pedestrian-oriented society. Therefore, the interest in pedestrian safety and the improvement of pedestrian environment is also increasing. However, the level of traffic safety in Korea is still severe. It is needed to improve pedestrian safety and pedestrian environment. This study studied pedestrian-vehicle accident data provided by the Traffic Accident Analysis System(TAAS) for 2013-2015 to build a safe walking environment around school zones, and the relation between the school zones and pedestrian-vehicle traffic accidents were identified through the geographic information system(GIS) and spatial regression model. The main results are as follows. First, both road and public transportation factors are likely to increase pedestrian traffic accidents in school zones. Second, regarding land-use factors, residential, commercial, and industrial areas are found to increase pedestrian traffic crashes. On the other hand, mixed use is likely to play a role on the reduction of pedestrian traffic accidents. Finally, it has been shown that high development density also has a positive effect on pedestrian traffic accidents in school zones.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.749-750
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• 2017

한국의 어린이 10만 명당 교통사고 사망자 비율은 약 1.3명으로 영국 0.5명, 일본 0.7명 등 OECD주요국보다 월등히 높다. 이에 스쿨존에서 어린이 교통사고 예방을 위한 스마트 보행자 안전보장 시스템을 개발하여 보행자와 운전자에게 위험 알림을 통해 사고를 예방할 수 있다.