• Title/Summary/Keyword: object detection system

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Lane Information Fusion Scheme using Multiple Lane Sensors (다중센서 기반 차선정보 시공간 융합기법)

  • Lee, Soomok;Park, Gikwang;Seo, Seung-woo
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.12
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    • pp.142-149
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    • 2015
  • Most of the mono-camera based lane detection systems are fragile on poor illumination conditions. In order to compensate limitations of single sensor utilization, lane information fusion system using multiple lane sensors is an alternative to stabilize performance and guarantee high precision. However, conventional fusion schemes, which only concerns object detection, are inappropriate to apply to the lane information fusion. Even few studies considering lane information fusion have dealt with limited aids on back-up sensor or omitted cases of asynchronous multi-rate and coverage. In this paper, we propose a lane information fusion scheme utilizing multiple lane sensors with different coverage and cycle. The precise lane information fusion is achieved by the proposed fusion framework which considers individual ranging capability and processing time of diverse types of lane sensors. In addition, a novel lane estimation model is proposed to synchronize multi-rate sensors precisely by up-sampling spare lane information signals. Through quantitative vehicle-level experiments with around view monitoring system and frontal camera system, we demonstrate the robustness of the proposed lane fusion scheme.

Development of a Backpack-Based Wearable Proximity Detection System

  • Shin, Hyungsub;Chang, Seokhee;Yu, Namgyenong;Jeong, Chaeeun;Xi, Wen;Bae, Jihyun
    • Fashion & Textile Research Journal
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    • v.24 no.5
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    • pp.647-654
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    • 2022
  • Wearable devices come in a variety of shapes and sizes in numerous fields in numerous fields and are available in various forms. They can be integrated into clothing, gloves, hats, glasses, and bags and used in healthcare, the medical field, and machine interfaces. These devices keep track individuals' biological and behavioral data to help with health communication and are often used for injury prevention. Those with hearing loss or impaired vision find it more difficult to recognize an approaching person or object; these sensing devices are particularly useful for such individuals, as they assist them with injury prevention by alerting them to the presence of people or objects in their immediate vicinity. Despite these obvious preventive benefits to developing Internet of Things based devices for the disabled, the development of these devices has been sluggish thus far. In particular, when compared with people without disabilities, people with hearing impairment have a much higher probability of averting danger when they are able to notice it in advance. However, research and development remain severely underfunded. In this study, we incorporated a wearable detection system, which uses an infrared proximity sensor, into a backpack. This system helps its users recognize when someone is approaching from behind through visual and tactile notification, even if they have difficulty hearing or seeing the objects in their surroundings. Furthermore, this backpack could help prevent accidents for all users, particularly those with visual or hearing impairments.

Multiple Camera-Based Real-Time Long Queue Vision Algorithm for Public Safety and Efficiency

  • Tae-hoon Kim;Ji-young Na;Ji-won Yoon;Se-Hun Lee;Jun-ho Ahn
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.10
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    • pp.47-57
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    • 2024
  • This paper proposes a system to efficiently manage delays caused by unmanaged and congested queues in crowded environments. Such queues not only cause inconvenience but also pose safety risks. Existing systems, relying on single-camera feeds, are inadequate for complex scenarios requiring multiple cameras. To address this, we developed a multi-vision long queue detection system that integrates multiple vision algorithms to accurately detect various types of queues. The algorithm processes real-time video data from multiple cameras, stitching overlapping segments into a single panoramic image. By combining object detection, tracking, and position variation analysis, the system recognizes long queues in crowded environments. The algorithm was validated with 96% accuracy and a 92% F1-score across diverse settings.

A Study on the System for AI Service Production (인공지능 서비스 운영을 위한 시스템 측면에서의 연구)

  • Hong, Yong-Geun
    • KIPS Transactions on Computer and Communication Systems
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    • v.11 no.10
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    • pp.323-332
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    • 2022
  • As various services using AI technology are being developed, much attention is being paid to AI service production. Recently, AI technology is acknowledged as one of ICT services, a lot of research is being conducted for general-purpose AI service production. In this paper, I describe the research results in terms of systems for AI service production, focusing on the distribution and production of machine learning models, which are the final steps of general machine learning development procedures. Three different Ubuntu systems were built, and experiments were conducted on the system, using data from 2017 validation COCO dataset in combination of different AI models (RFCN, SSD-Mobilenet) and different communication methods (gRPC, REST) to request and perform AI services through Tensorflow serving. Through various experiments, it was found that the type of AI model has a greater influence on AI service inference time than AI machine communication method, and in the case of object detection AI service, the number and complexity of objects in the image are more affected than the file size of the image to be detected. In addition, it was confirmed that if the AI service is performed remotely rather than locally, even if it is a machine with good performance, it takes more time to infer the AI service than if it is performed locally. Through the results of this study, it is expected that system design suitable for service goals, AI model development, and efficient AI service production will be possible.

Efficient Eye Location for Biomedical Imaging using Two-level Classifier Scheme

  • Nam, Mi-Young;Wang, Xi;Rhee, Phill-Kyu
    • International Journal of Control, Automation, and Systems
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    • v.6 no.6
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    • pp.828-835
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    • 2008
  • We present a novel method for eye location by means of a two-level classifier scheme. Locating the eye by machine-inspection of an image or video is an important problem for Computer Vision and is of particular value to applications in biomedical imaging. Our method aims to overcome the significant challenge of an eye-location that is able to maintain high accuracy by disregarding highly variable changes in the environment. A first level of computational analysis processes this image context. This is followed by object detection by means of a two-class discrimination classifier(second algorithmic level).We have tested our eye location system using FERET and BioID database. We compare the performance of two-level classifier with that of non-level classifier, and found it's better performance.

Detection of Tongue Area using Active Contour Model (능동 윤곽선 모델을 이용한 혀 영역의 검출)

  • Han, Young-Hwan
    • Journal of rehabilitation welfare engineering & assistive technology
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    • v.10 no.2
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    • pp.141-146
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    • 2016
  • In this paper, we apply limited area mask operation and active contour model to accurately detect tongue area outline in tongue diagnosis system. To accurately analyze the properties of the tongue, first, the tongue area to be detected. Therefore an effective segmentation method for detecting the edge of tongue is very important. It experimented with tongue image DB consists of 20~30 students 30 people. Experiments on real tongue image show the good performance of this method. Experimental results show that the proposed method extracts object boundaries more accurately than existing methods without mask operation.

Object Detection based on Image Processing for Indoor Drone Localization (실내 드론의 위치 추정을 위한 영상처리 기반 객체 검출)

  • Beck, Jong-Hwan;Kim, Sang-Hoon
    • Annual Conference of KIPS
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    • 2017.04a
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    • pp.1003-1004
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    • 2017
  • 본 연구에서는 실내 환경에서 드론의 측위를 위한 마커 인식 및 검출 기술을 소개한다. 기존 실내 측위를 위한 기술인 Global Positioning System이나 Wi-Fi를 이용한 삼각측량 기법은 실내 환경에서 각각의 성질로 인하여 사용하기 어려운 점이 있다. 본 논문에서는 2차원 바코드와 마커 등의 객체를 드론의 카메라를 이용한 실시간 영상 전송을 통하여 검출하여 위치 정보를 획득하는 기술을 소개한다. 실험에서는 드론의 카메라를 통하여 실시간 전송된 영상에서 OpenCV V2.4.10을 통하여 객체를 검출하였고, 카메라와 객체 사이의 거리와 바코드 크기에 따른 2차원 바코드의 검출 여부를 보였으며 15*15cm의 2차원 바코드는 비교적 잘 인식하였으나 비교적 작은 11*11cm의 2차원 바코드는 거리가 멀어질 수록 인식이 힘들어지는 결과를 보였다.

Metal Object Detection System for Protecting the Driver in Car (내부 운전자 보호를 위한 금속물체 탐지 시스템)

  • Kim, Jin-Kyu;Joo, Young-Hoon;Park, Jin-Bae
    • Proceedings of the KIEE Conference
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    • 2009.07a
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    • pp.1843_1844
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    • 2009
  • 본 논문에서는 영상처리 기술을 기반으로 한 내부 운전자에게 위협이 될 수 있는 금속 물체를 탐지하기 위한 실시간 시스템을 제안한다. 제안된 시스템은 퍼지 이론을 이용하여 금속물체를 탐지할 수 있는 색상 필터를 설계하여 사용하였다. 차량안의 특정 탐지 영역 내에서 FCF(Fuzzy Skin Filter)를 이용하여 운전자의 얼굴 영역을 탐지하고, 동승자가 위협을 가한다는 가정 하에 손 영역을 탐지한다. 탐지된 동승자의 손 영역을 중심으로 색상기반 원형 탐색기법을 사용하여 최종 금속물체의 후보영역을 설정하고, 금속물체 색상필터를 적용하여 최종적인 금속물체영역을 탐지 한다. 제안된 방법은 여러 실험을 통해 내부 운전자 보호를 위한 금속물체 탐지 시스템의 우수성을 증명한다.

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Femto Slider Head/Disk Interaction Detection by Acoustic Emission and Natural Frequency Analysis

  • Hwang, Pyung;Galina Pan;Xuan Wu
    • KSTLE International Journal
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    • v.6 no.1
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    • pp.17-20
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    • 2005
  • The object of the present work is the natural lre%uency analysis of femto slider, HeaHdisk interaction during starustop and constant speed were detected by using the acoustic emission (AE) test system. The frequency spectrum analysis wasperformed using the AE signal obtained during the head/disk interaction. The FFT (Fast Fourier Transform) analysis of the AEsignals is used to understand the interaction between the AE signal and the state of contact. Natural frequency analysis wasperformed using the ANSYS program. The results indicate acceptable accordance of finite element calculation results with theexperimental results.

Study on Water Leakage Detection System on PDA Environment (PDA환경에서의 누수탐지시스템에 관한 연구)

  • 정대권;홍인식
    • Proceedings of the Korea Multimedia Society Conference
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    • 2003.11b
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    • pp.1014-1017
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    • 2003
  • 한국의 수자원은 높은 인구밀도와 물을 담아 관리하는 시설 및 물에 대한 인식 부족으로 물 부족 현상은 현실로 다가오고 있다. 또한 많은 양의 정수가 사용하지도 못한 채 땅속에서 새어나가고 있으며, 이를 관리 및 탐지하는 방법에도 많은 제약사항이 있어 빠른 복구와 대처능력이 현저히 부족하다. 본 논문은 모바일의 장점인 이동성을 이용하여 누수탐지 기법중의 하나인 'TDR(Time Domain Reflectomater)을 이용한 누수탐지 기법'을 PDA에 적용시켜 모바일 환경에서도 정확한 누수위치를 탐색하여 빠른 복구와 누수 비용을 줄이는데 목적이 있다 누수위치와 복구공사에 관련된 정보들은 PDA로 전송되며, 관리자는 복구공사에 대한 빠른 대처능력과 의사결정을 할 수 있다. 본 연구의 유효성을 입증하기 위하여 ESRI사의 MapObject 2.0과 eVB를 이용하여 PDA환경에서의 누수탐지 시스템을 시뮬레이션 하였다.

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