• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.410-412
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• 2021

This paper proposes an improved pedestrian detection method using object and background histograms. Objects detected through the HOG & SVM algorithm are detected in a square shape. Inside the square area, the background and the object area are mixed. If only the area of the object excluding the background is detected, various object-related information may be easily obtained. The size of the detected rectangle is readjusted using an xy-axis projection algorithm to fit the size of the object. And then, the improved object is detected by dividing the background and the object based on the histogram of the object in the readjusted square. The average values of precision and recall, which are reliability evaluations comparing the detected object with the original object, are 97.9% and 90%, respectively.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.2
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• pp.239-246
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• 2015

Video based object detection is basic technology of implementing smart CCTV system. Various features and algorithms are developed to detect object, however computations of them increase with the performance. In this paper, performances of object detection algorithms with GPU and CPU are compared. Adaboost and SVM algorithm which are widely used to detect pedestrian detection are implemented with CPU and GPU, and speeds of detection processing are compared for the same video. As results of frame rate comparison of Adaboost and SVM algorithm, it is shown that the frame rate with GPU is faster than CPU.

• Journal of Broadcast Engineering
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• v.20 no.3
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• pp.440-448
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• 2015

A pedestrian collision warning system which makes a judgement of pedestrian's intention to help avoiding hitting accidents is proposed. This system uses the image sequences obtained from a car black box as well as vehicle's speed obtained from a GPS. It detects pedestrians, if any, based on the Histogram of Gradient method and extracts several information such as the pedestrian's relative positions, the direction of motion vectors, and distance between vehicle and pedestrian . A fuzzy logic based on these extracted information is applied to analyze the pedestrian's safety levels. When the safety level is determined to be danger, an alarm is triggered to the driver. The performance of the proposed algorithm is tested under various driving scenarios, which shows it works successfully in real-time.

• Journal of IKEEE
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• v.18 no.1
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• pp.106-113
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• 2014

A pedestrian detector can be applied for various purposes such as monitoring or counting the number of people in some place, or detecting the people plunging in the driveway. There was a lot of related research. But, the detection speed is slow in embedded system because of the limited computing power. An algorithm for fast pedestrian detector using HOG in ARM SIMD architecture is presented in this paper. There is a way to quickly remove the background of image and to improve the detection speed using NEON parallel technique. When we tested with INRIA Person Dataset, the proposed pedestrian detector improves the speed by 3.01 times than previous one.

• 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 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.76-79
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• 2016

자동차 산업의 발달과 전세계적으로 차량의 증가로 인해 보행자의 사고 발생율이 증가하고 있고 보행자의 안전에 대해 연구와 안전장비들이 계속적으로 개발되고 있다. 보행자와 차량의 충돌시 보행자의 상해를 감소시키는 시스템 중 화약식 액티브 후드 시스템(active hood system, AHS)은 부하가 화약성분이므로 부하의 성분을 검출하는데 한계가 있고, 위험성이 높으므로 정밀한 고장진단이 필요하다. 이러한 문제점을 해결하기 위해 화약의 부하저항을 측정하는 방법과 저항성 누설전류를 측정하는 방법을 제시하고, 이 방법을 점화회로의 이상 유무를 확인하는 고장진단 기법으로 제안한다. 그리고 고장진단시 squib가 점화되는 오동작을 방지하고저 고장진단 모드와 점화모드를 구별하여 진단전류와 점화전류를 구분하는 기법을 제안한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1551-1553
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• 2013

지능형 영상감시에 대한 연구와 개발이 가속화되면서, 화재감시에 대한 예방 및 경보시스템 또한 빠른 속도로 발전하고 있다. 그러나, 기존시스템은 화재에 대한 감시기능에만 국한되어 있어, 기능으로써의 한계점을 가지고 있다. 따라서 본 논문에서는 이러한 문제점을 해결하기위해, 본 논문에서는 화재와 보행자를 검출하여, 초기대응 및 화재원인에 대한 정보를 제공하며, 보행자에 대한 안전을 최대한 보장할 수 있는 화재현장 보행자 인식을 통한 지능형 영상인식 시스템을 설계하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.1C
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• pp.26-35
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• 2006

In this paper, an automatic mobile robot system for a intelligent path planning using the detection scheme of the spatial coordinates based on stereo camera is proposed. In the proposed system, face area of a moving person is detected from a left image among the stereo image pairs by using the YCbCr color model and its center coordinates are computed by using the centroid method and then using these data, the stereo camera embedded on the mobile robot can be controlled for tracking the moving target in real-time. Moreover, using the disparity map obtained from the left and right images captured by the tracking-controlled stereo camera system and the perspective transformation between a 3-D scene and an image plane, depth information can be detected. Finally, based-on the analysis of these calculated coordinates, a mobile robot system is derived as a intelligent path planning and a estimation. From some experiments on robot driving with 240 frames of the stereo images, it is analyzed that error ratio between the calculated and measured values of the distance between the mobile robot and the objects, and relative distance between the other objects is found to be very low value of $2.19\%$ and $1.52\%$ on average, respectably.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.9
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• pp.4131-4138
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• 2012

In this paper, we propose a Pedestrian Position Information System(PPIS) using low-cost inertial sensors in GPS-disabled area. The proposed scheme estimates the attitude/heading angle and step detection of pedestrian. Additionally, the estimation error due to the inertial sensors is mitigated by using additional sensors. We implement a portable hardware module to evaluate performance of the proposed system. Through the experiments in indoor building, the estimation error of position information was measured as 2.4% approximately.