• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.2
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• pp.183-188
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• 2015

In this paper, it is proposed to detect and track pedestrian and analyse tracking performance with nighttime CCTV video. The detection is performed by a cascade classifier with Haar-like feature trained with Adaboost algorithm. Tracking pedestrian is performed by a particle filter. As results of experiments, it is introduced that efficient number of particles and the distributions are applied to track pedestrian at the night-time. Performance of detection and tracking is verified with nighttime CCTV video that is obtained at alleys etc.

• Journal of information and communication convergence engineering
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• v.19 no.3
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• pp.188-197
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• 2021

In military operations, an accurate localization system is required to navigate soldiers to their destinations, even in non-GPS environments. The global positioning system is a commonly used localization method, but it is difficult to maintain the robustness of GPS-based localization against jamming of signals. In addition, GPS-based localization cannot provide important terrain information such as obstacles. With the widespread use of embedded sensors, sensor-based pedestrian tracking schemes have become an attractive option. However, because of noisy sensor readings, pedestrian tracking systems using motion sensors have a major drawback in that errors in the estimated displacement accumulate over time. We present a group-based standalone system that creates terrain maps automatically while also locating soldiers in mountainous terrain. The system estimates landmarks using inertial sensors and utilizes split group information to improve the robustness of map construction. The evaluation shows that our system successfully corrected and combined the drift error of the system localization without infrastructure.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.4
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• pp.812-820
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• 2012

In this paper, multiple pedestrians tracking system using Histogram of Oriented Gradient and occlusion detection is proposed. The proposed system is applicable to Intelligent Surveillance System. First, we detect pedestrian in a image sequence using pedestrian's feature. To get pedestrian's feature, we make block-histogram using gradient's direction histogram based on HOG(Histogram of Oriented Gradient), after that a pedestrian region is classified by using Linear-SVM(Support Vector Machine) training. Next, moving objects are tracked by using position information of the classified pedestrians. And we create motion trajectory descriptor which is used for content based event retrieval. The experimental results show that the proposed method is more fast, accurate and effective than conventional methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.4
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• pp.641-647
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• 2018

Recently, CCTV, which provides video information for multiple purposes, has been transformed into an intelligent, and the range of automation applications increased using the computer vision. A highly reliable detection method must be performed for accurate recognition of pedestrians and vehicles and various methods are being studied for this purpose. In such an object detection system. In this paper, we propose a method to detect a large number of pedestrians by acquiring three characteristic information that features of color information using HSI, motion vector information and shaping information using HOG feature information of a pedestrian in a situation where a large number of pedestrians are moving. The proposed method distinguishes each pedestrian while minimizing the failure or confusion of pedestrian detection and tracking. Also when pedestrians approach or overlap, pedestrians are identified and detected using stored frame feature data.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.11
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• pp.1017-1021
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• 2013

The traffic signal has been widely used in the transport system with a fixed time interval currently. This kind of setting time was determined based on experience for vehicles to generate a waiting time while allowing pedestrians crossing the street. However, this strict setting causes inefficient problems in terms of economic and safety crossing. In this research, we propose a monitoring algorithm to detect, track and check pedestrian crossing the crosswalk by the patterns of behavior. This monitoring system ensures the safety for pedestrian and keeps the traffic flow in efficient. In this algorithm, pedestrians are detected by using HOG feature which is robust to illumination changes in outdoor environment. According to a complex computation, the parallel process with the GPU as well as CPU is adopted for real-time processing. Therefore, pedestrians are tracked by the relationship of hue channel in image sequence according to the predefined pedestrian zone. Finally, the system checks the pedestrians' crossing on the crosswalk by its HOG based behavior patterns. In experiments, the parallel processing by both GPU and CPU was performed so that the result reaches 16 FPS (Frame Per Second). The accuracy of detection and tracking was 93.7% and 91.2%, respectively.

• Annual Conference of KIPS
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• 2016.04a
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• pp.640-641
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• 2016

There are a number of reported papers about detection and tracking of pedestrian for urban design. While related studies have not dealt with various environmental situations, this paper proposes a pedestrian counting system using pedestrian pattern for overcoming technical limitations. The Pedestrian Algorithm uses four steps to count the number of pedestrians for analyzing the pedestrian pattern according to the characteristics of the foot patterns of pedestrians.

• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.5
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• pp.124-133
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• 2014

This study aims to track pedestrian behavior in urban linear tourist sites and to analyse their behavioral characteristics. For these purposes, this study has adopted the direct observation, a behavioral tracking methodology, and selected Chenggyecheon in Seoul as the study site, a representative site of urban regeneration. The main results of this study can be summarized as follows: the period of stay and movement distance of pedestrians in the study area are both short and most pedestrian activities, apart from walking, are of a passive nature, such as pitching pennies, reading signs, resting and the like. Spatial points of Chenggyecheon at which pedestrians have exhibited these behaviors during their stay are summarized as 30 points and classified into 3 types: landmarks, bridges and nodes. Further research that combines several tracking methods in terms of urban pedestrian behavior is needed.

• Proceedings of the Korean Institute of Interior Design Conference
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• 2001.05a
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• pp.157-162
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• 2001

This Research analyzed with itinerary tracking : two of each other shopping sites were selected as research point. Analyzing the result, pedestrian path choice is affected by direction of escalator, visual information of the object, plain form of passage, presence and absence of companion and proportion of spatial knowledge from experience. The factors affecting pedestrian path choice are divided into two groups which are the effects from the environment, and personal characteristics.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.3
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• pp.187-192
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• 2015

Detecting human in images is a challenging task owing to their variable appearance and the wide range of poses the they can adopt. The first need is a robust feature set that allows the human form to be discriminated cleanly, even in cluttered background under difficult illumination. A large number of vision application rely on matching keypoints across images. These days, the deployment of vision algorithms on smart phones and embedded device with low memory and computation complexity has even upped the ante: the goal is to make descriptors faster compute, more compact while remaining robust scale, rotation and noise. In this paper we focus on improving the speed of pedestrian(walking person) detection using Histogram of Oriented Gradient(HOG) descriptors provide excellent performance and tracking using kalman filter.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.435-442
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• 2015

In this paper, we propose a tracking and recognition of pedestrian/vehicle for intelligent multi-visual surveillance system. The intelligent multi-visual surveillance system consists of several fixed cameras and one calibrated PTZ camera, which automatically tracks and recognizes the detected moving objects. The fixed wide-angle cameras are used to monitor large open areas, but the moving objects on the images are too small to view in detail. But, the PTZ camera is capable of increasing the monitoring area and enhancing the image quality by tracking and zooming in on a target. The proposed system is able to determine whether the detected moving objects are pedestrian/vehicle or not using the SVM. In order to reduce the tracking error, an improved camera calibration algorithm between the fixed cameras and the PTZ camera is proposed. Various experimental results show the effectiveness of the proposed system.