• Title/Summary/Keyword: 적외선 센서 기반 물체 추적

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Tracking of Multi-targets in CCD/IR Multi-sensor system for ITS application (CCD/IR 영상에서의 다중 센서 다중 표적 추적)

  • 이일광;고한석
    • Proceedings of the IEEK Conference
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    • 2001.09a
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    • pp.359-362
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    • 2001
  • 본 논문에서는 광학센서와 적외선 센서를 사용하는 Multi-sensor 시스템에서 영상 정보를 통한 물체의 추적 및 인식에 필요한 영상을 분리하는데 필요한 전처리와 object 기반의 추적 방법을 제안하였다. 일반적인 추적 알고리즘의 목표는 consistency를 유지하는데 있다. 그러나 인식에 필요한 영상을 분리하기 위해서는 물체의 범위를 정확히 판단 할 수 있는 능력이 중요하다. 이를 위해 CCD와 IR영상에 동시에 적용 가능한 전처리 기법과 object 기반의 two-step 추적 알고리즘을 통해 consistency외에도, 물체의 범위를 estimation하여 인식에 필요한 범위를 분리해 낸다. 본 논문에서는 ITS 의 ETCS application을 위해 이종 센서인 CCD와 IR의 야간 차량 영상정보를 이용하여 알고리즘을 test 하였다.

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A Precise Tracking System for Dynamic Object using IR sensor for Spatial Augmented Reality (공간증강현실 구현을 위한 적외선 센서 기반 동적 물체 정밀 추적 시스템)

  • Oh, JiSoo;Park, Jinho
    • Journal of the Korea Computer Graphics Society
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    • v.23 no.3
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    • pp.115-122
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    • 2017
  • As the era of the fourth industrial revolution began, augmented reality showed infinite possibilities throughout society. However, current augmented reality systems such as head-mount display and hand-held display systems suffer from various problems such as weariness and nausea, and thus space-augmented reality, which is a projector-based augmented reality technology, is attracting attention. Spacial augmented reality requires precise tracking of dynamic objects to project virtual images in order to increase realism of augmented reality and induce user 's immersion. The infrared sensor-based precision tracking algorithm developed in this paper demonstrates very robust tracking performance with an average error rate of less than 1.5% and technically opens the way towards advanced augmented reality technologies such as tracking for arbitrary objects, and Socially, by easy-to-use tracking algorithms for non-specialists, it allows designers, students, and children to easily create and enjoy their own augmented reality content.

An Adaptive Person/Vehicle Detection Algorithm for PIR Sensor (적외선 센서 기반의 사람/차량 탐지 적응 알고리즘)

  • Kim, Young-Man;Park, Jang-Ho;Kim, Li-Hyung;Park, Hong-Jae
    • Journal of KIISE:Computing Practices and Letters
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    • v.15 no.8
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    • pp.577-581
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    • 2009
  • Recently, various new services based on ubiquitous computing and networking have been developed. In this paper, we contrive Adaptive PIR(Pyroelectric Infrared Radiation) Detection Algorithm (APIDA), a PIR-sensor based digital signal processing algorithm, that detects the movement of an invading object by the recognition of heat change in the detection area, since the object like person or car emits heat(i.e., infrared radition), We devised APIDA as a highly reliable signal processing algorithm that increases the successful detection rate and decreases the false alarm rate in the intruding object detection. According to performance evaluation experiment, APIDA shows the successful detection rate of 90% and low false alarm in the plain area.

Development of A Multi-sensor Fusion-based Traffic Information Acquisition System with Robust to Environmental Changes using Mono Camera, Radar and Infrared Range Finder (환경변화에 강인한 단안카메라 레이더 적외선거리계 센서 융합 기반 교통정보 수집 시스템 개발)

  • Byun, Ki-hoon;Kim, Se-jin;Kwon, Jang-woo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.16 no.2
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    • pp.36-54
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    • 2017
  • The purpose of this paper is to develop a multi-sensor fusion-based traffic information acquisition system with robust to environmental changes. it combines the characteristics of each sensor and is more robust to the environmental changes than the video detector. Moreover, it is not affected by the time of day and night, and has less maintenance cost than the inductive-loop traffic detector. This is accomplished by synthesizing object tracking informations based on a radar, vehicle classification informations based on a video detector and reliable object detections of a infrared range finder. To prove the effectiveness of the proposed system, I conducted experiments for 6 hours over 5 days of the daytime and early evening on the pedestrian - accessible road. According to the experimental results, it has 88.7% classification accuracy and 95.5% vehicle detection rate. If the parameters of this system is optimized to adapt to the experimental environment changes, it is expected that it will contribute to the advancement of ITS.