• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1839-1845
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• 2016

Detecting remote targets is important to active protection system (APS) or infrared search and track (IRST) applications. In normal situation, the well-known constant false alarm rate (CFAR) detector works properly. However, decoys in APS or closely spaced targets in IRST degrade the detection capability by increasing background noise level in the CFAR detector. This paper presents a context aware CFAR detector by the intensity sorting and selection of background region to reduce the effect of neighboring targets that lead to incorrect estimation of background statistics. The existence of neighboring targets can be recognized by intensity sorting where neighboring targets usually show highest ranks. The proposed background statistics (mean, standard deviation) estimation method from median local pixels can be aware of the background context and reduce the effects of the neighboring targets, which increase the signal-to-clutter ratio. The experimental results on the synthetic APS sequence, real adjacent target sequence, and remote pedestrian sequence validated that the proposed method produced an enhanced detection rate with the same false alarm rate compared with the hysteresis-CFAR (H-CFAR) detection.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.5
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• pp.35-49
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• 2014

This paper proposes the on-road object detection and classification algorithm by using a detection system consisting of only laser scanners. Each sensor data acquired by the laser scanner is fused with a grid map and the measurement error and spot spaces are corrected using a labeling method and dilation operation. Fuzzy method which uses the object information (length, width) as input parameters can classify the objects such as a pedestrian, bicycle and vehicle. In this way, the accuracy of the detection system is increased. Through experiments for some scenarios in the real road environment, the performance of the proposed detection and classification system for the actual objects is demonstrated through the comparison with the actual information acquired by GPS-RTK.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.3
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• pp.167-174
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• 2008

This paper presents the technology trend of various active safety systems for vehicle. The safety system is applied to various industry fields and is expected to be spread all over the market. So far, good examples of the developed active safety systems are ACC(Adaptive Cruise Control), CMS(Collision Mitigation Systems) and APSS(Active Pedestrian Safety Systems). And, a basic operation principle, system model and detection performance in a UWB radar for vehicle is investigated.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.11a
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• pp.15-16
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• 2012

본 논문에서는 중요도 맵을 이용하여 기존 보행자 검출 시스템의 성능을 향상시키는 기법을 제안한다. 기존 보행자 검출시스템이 수직 성분이 강한 물체를 보행자로 잘못 검출하는 문제를 개선하기 위해 제안하는 기법에서는 중요도 맵 정보를 이용하여 보행자가 아닌 배경 부분을 제외시킴으로써 보행자 검출 성능을 향상 시킨다. 실험결과를 통해 제안하는 기법의 성능을 확인한다.

• Journal of the HCI Society of Korea
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• v.14 no.2
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• pp.41-47
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• 2019

In this study, a smart assistive device is designed to recognize pedestrian signal and to provide audio instructions for visually impaired people in crossing streets safely. Walking alone is one of the biggest challenges to the visually impaired and it deteriorates their life quality. The proposed device has a camera attached on a pair of glasses which can detect traffic lights, recognize pedestrian signals in real-time using a machine learning algorithm on GPU board and provide audio instructions to the user. For the portability, the dimension of the device is designed to be compact and light but with sufficient battery life. The embedded processor of device is wired to the small camera which is attached on a pair of glasses. Also, on inner part of the leg of the glasses, a bone-conduction speaker is installed which can give audio instructions without blocking external sounds for safety reason. The performance of the proposed device was validated with experiments and it showed 87.0% recall and 100% precision for detecting pedestrian green light, and 94.4% recall and 97.1% precision for detecting pedestrian red light.

• Journal of the Ergonomics Society of Korea
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• v.31 no.3
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• pp.421-426
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• 2012

As headlamp technology advances, newly developed various headlamps were introduced in the market. The objective of this study is to quantitatively analyze the detection distance of the recently developed LED headlamps and existing headlamps, complying with specific technical standard. Background: The detection distance of headlamps is very important to prevent automobile accident at night time. The studies of detection distance of LED, Halogen and HID headlamp have been conducted, but no study has shown the detection distance of pedestrian target with various colors (Black, White, Blue). Method: The experiment of detection distance was conducted with 30 people, which divide into 2 groups as 15 men and 15 women. Automatic transferable target on the rail was manufactured in order to reduce the error of study's result, and ANOVA also conducted to analyze the main effect with sign color, sex and headlamp classified by detection distance. In addition, the luminance by average detection distance was measured as well. Results: The detection distance of headlamps was HID > LED > Halogen. The luminance measure of LED headlamp was lower than HID and Halogen headlamps. Conclusion: The headlamp performs a very significant role for safety at night time but it needs to be improved through assessment of visual characteristics. Also, it needs to be suggested the need of test method for dynamic detection distance concerning technical development is suggested.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.9
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• pp.1082-1087
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• 2019

Video Incident Detection System is a detection system for the purpose of detection of an emergency in an unexpected situation such as a pedestrian in a tunnel, a falling object, a stationary vehicle, a reverse run, and a fire(smoke and flame). In recent years, the importance of the city center has been emphasized by the construction of underpasses in great depth underground space. Therefore, in order to apply Video Incident Detection System to a Double Deck Tunnel, it was developed to reflect the design characteristics of the Double Deck Tunnel. and In this paper especially, the fire detection technology, which is not it is difficult to apply to the Double Deck Tunnel environment because it is not supported on existing Video Incident Detection System or has a fail detect, we propose fire detection using color image analysis, silhouette spread, and statistical properties, It is verified through a real fire test in a double deck tunnel test bed environment.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.1
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• pp.33-42
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• 2020

In Integration Approach (IA)-based Pedestrian Dead Reckoning (PDR), it is important to detect the exact zero-velocity of the foot with an Inertial Measurement Unit (IMU). By detecting zero-velocity during the stance phase of the foot touching the ground and executing Zero-velocity UPdaTe (ZUPT) at the exact time, stable navigation information can be provided by the PDR. When the pace is fast, however, it is not easy to accurately detect the zero-velocity because of the small stance phase interval and the large signal variance of the corresponding interval. Incorrect zero-velcity detection greatly causes navigation errors of IA-based PDR. In this paper, we propose a method to detect the zero-velocity stably even at high speed by novel buffering of IMU's output data and signal processing of the buffer. And we design a PDR based on this. By analyzing the performance of the proposed Zero-Velocity Detection (ZVD) algorithm and ZVD-based PDR through experiemnts, we confirm that the proposed method can provide accurate navigation information of pedestrians such as firefighters in the indoor space.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.12
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• pp.5873-5877
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• 2011

In this paper, we propose a study of analysis to the mobility of object such like pedestrian in safety management zone. If unusual situation is detected in safety management zone, it's designed that previous agreed mission will be processed. By human resource, safety management zone cannot be detected continuously so that through the induction of such detection system the reliability of area can be obtained. Hence, in this paper we propose the reaction scheme to detect special situation by object detection. By using sensor based processing system proposed by this paper, the detection of mobility and unusual situation can be implemented.

• International Journal of Advanced Culture Technology
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• v.10 no.2
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• pp.300-306
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• 2022

Currently, Korea is building traffic infrastructure using Intelligent Transport Systems (ITS), but the pedestrian traffic accident rate is very high. The purpose of this paper is to prevent the risk of traffic accidents by jaywalking pedestrians. The development of this study aims to detect pedestrians who trespass using the public data set provided by the Artificial Intelligence Hub (AIHub). The data set uses training data: 673,150 pieces and validation data: 131,385 pieces, and the types include snow, rain, fog, etc., and there is a total of 7 types including passenger cars, small buses, large buses, trucks, large trailers, motorcycles, and pedestrians. has a class format of Learning is carried out using YOLOv5 as an implementation model, and as an object detection and edge detection method of an input image, a canny edge model is applied to classify and visualize human objects within the detected road boundary range. In this study, it was designed and implemented to detect pedestrians using the deep learning-based YOLOv5 model. As the final result, the mAP 0.5 showed a real-time detection rate of 61% and 114.9 fps at 338 epochs using the YOLOv5 model.