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Conference on Electro-Optical and infrared Systems - technology and Applications XIII

作者： Rodger, Iain Connor, Barry Robertson, Neil M. Heriot Watt Univ Sch Engn & Phys Sci Riccarton EH14 4AS Midlothian Scotland Thales UK 1 Linthouse Rd Glasgow G51 4BZ Lanark Scotland Queens Univ Belfast Sch Elect Elect Engn & Comp Sci Belfast BT7 1NN Antrim North Ireland

ISBN: (数字)9781510603790

ISBN: (纸本)9781510603783;9781510603790

The aim of the presented work is to demonstrate enhanced target recognition and improved false alarm rates for a mid to long range detection system, utilising a Long Wave infrared (LWIR) sensor. By exploiting high quality thermal image data and recent techniques in machine learning, the system can provide automatic target recognition capabilities. A Convolutional Neural Network (CNN) is trained and the classifier achieves an overall accuracy of > 95% for 6 object classes related to land defence. While the highly accurate CNN struggles to recognise long range target classes, due to low signal quality, robust target discrimination is achieved for challenging candidates. The overall performance of the methodology presented is assessed using human ground truth information, generating classifier evaluation metrics for thermal image sequences.

关键词： LongWave Thermal-infrared Object classification Convolutional Neural Network Machine Learning

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基于YOLO网络模型的异常行为检测方法研究

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电子设计工程 2018年第20期26卷 154-158,164页

作者：刘雪奇孙胜利中国科学院上海技术物理研究所上海200083 中国科学院大学北京100049 上海科技大学上海201210 中国科学院红外探测与成像技术重点实验室上海200083

针对监控视频中人体异常行为的复杂多样难检测问题,提出了基于YOLO网络模型的异常行为检测方法。根据对监控场景的异常行为定义需求,将标定的异常行为通过YOLO网络模型进行训练,不进行人体目标的提取而将其放到神经网络中,直接实现端到... 详细信息

针对监控视频中人体异常行为的复杂多样难检测问题,提出了基于YOLO网络模型的异常行为检测方法。根据对监控场景的异常行为定义需求,将标定的异常行为通过YOLO网络模型进行训练,不进行人体目标的提取而将其放到神经网络中,直接实现端到端的异常行为分类,从而实现对具体应用场景的异常行为检测。实验结果表明,该方法召回率接近100%并且平均精确率达到96%以上,同时通过GPU加速对于视频流的检测速度可以达到30FPS左右,实现对监控视频异常行为的实时检测。

关键词： YOLO 异常行为识别框 IOU 召回率精确率

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基于红外图像识别的输电线路故障诊断方法

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红外技术 2017年第4期39卷 383-386页

作者：王淼杜伟孙鸿博张静国网通用航空有限公司北京100005 天津航天中为数据系统科技有限公司天津市智能遥感信息处理技术企业重点实验室天津300301

基于红外图像研究了输电线路的故障诊断方法,首先采用LSD线段检测法提取红外图像中的导线,采用深度卷积神经网络提取红外图像中绝缘子,从而得到线路元件区域。在线路元件区域内进行温度和灰度分析提取发热点,并利用漫水填充算法对过热... 详细信息

基于红外图像研究了输电线路的故障诊断方法,首先采用LSD线段检测法提取红外图像中的导线,采用深度卷积神经网络提取红外图像中绝缘子,从而得到线路元件区域。在线路元件区域内进行温度和灰度分析提取发热点,并利用漫水填充算法对过热区域进行分割,提取骨架扫描点数、有效凸缺陷、引流线对缺陷类型进行识别。实验证明该算法有较高发热点定位准确率和缺陷类型识别准确率。

关键词：红外图像输电线巡检导线提取绝缘子检测缺陷点定位特征提取缺陷识别

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Dim moving target detection algorithm based on spatio-temporal classification sparse representation

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infrared PHYSICS & technology 2014年 67卷 273-282页

作者： Li, Zhengzhou Dai, Zhen Fu, Hongxia Hou, Qian Wang, Zhen Yang, Lijiao Jin, Gang Liu, Changju Li, Ruzhang Chongqing Univ Coll Commun Engn Chongqing 400044 Peoples R China China Aerodynam Res & Dev Ctr Mianyang 621000 Sichuan Peoples R China China Elect Technology Grp Corp Sichuan Inst Solid State Circuits Res Inst 24 Natl Lab Analogue Integrated Circuits Chongqing 400060 Peoples R China

A dim moving target detection algorithm based on spatio-temporal classification sparse representation, which can characterize the motion information and morphological feature of target and background clutter, is proposed to enhance the performance of target detection. A spatio-temporal redundant dictionary is trained according to the content of infrared image sequence, and then is subdivided into target spatio-temporal redundant dictionary describing moving target, and background spatio-temporal redundant dictionary embedding background by the criterion that the target spatio-temporal atom could be decomposed more sparsely over Gaussian spatio-temporal redundant dictionary. The target and background clutter can be sparsely decomposed over their corresponding spatio-temporal redundant dictionary, yet could not be sparsely decomposed on their opposite spatio-temporal redundant dictionary, and so their residuals after reconstruction by the prescribed number of target and background spatio-temporal atoms would differ very visibly. Some experimental results show this proposed approach could not only improve the sparsity more efficiently, but also enhance the target detection performance more effectively. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Dim target detection Spatio-temporal classification redundant dictionary target spatio-temporal redundant dictionary Background spatio-temporal redundant dictionary Signal sparse reconstruction

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Research on technology of target real-time detection under Sea-sky background

Research on Technology of Target real-time Detection under S...

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Conference on Applied Optics and Photonics (AOPC) - Image Processing and Analysis

作者： Wang Shiyun Li Yueqiang Du Bin Wang Hongtao Han Rui Jiangsu North HUGON Opt & Elect Ltd CO Wuxi 214035 Peoples R China Naval Acad Armament Beijing 1000161 Peoples R China

ISBN: (纸本)9781628419009

Optoelectronic imaging system which loaded on ships have several imaging channels generally. They can cover visible light (daylight and low-light), medium wave infrared and long wave infrared. To that systems have only two channels, visible light imaging is kept. In this paper, for the requirement of target real-time detection and classification under sea-sky background, image data from different channels are processed independently using Harris feature of targets and texture feature of background, then the result data from different channels are fused and compared to delete fake targets and interference from background, in order to reduce false alarm rate and improve the detection location precision. Based on the location relationship between targets and different type background (sky or sea), the target types are determined. For the rigidly requirement of system real time, multithread mechanism and big neighborhood processor are applied for parallel data processing, in order to reduce the processing time less than one frame time. At last, the experiment has been done on two channels system, approving that the method in this paper can improve the comprehensive searching performance of optoelectronic imaging system.

关键词： target real-time detection sea-sky background real-time system

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遥感图像中微小红外目标的分类定位识别

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科技通报 2015年第12期31卷 231-233页

作者：高照忠魏海霞喻怀义广东工贸职业技术学院广东510510

遥感图像中存在大量微小红外目标,对其准确的分类和定位识别是实现远程目标识别和遥感测量的基础。目前对该类红外小目标的识别方法采用单层正方形网格生成方法,对随机标定的红外目标点的识别效果不好。提出一种基于Harris角点检测的遥... 详细信息

遥感图像中存在大量微小红外目标,对其准确的分类和定位识别是实现远程目标识别和遥感测量的基础。目前对该类红外小目标的识别方法采用单层正方形网格生成方法,对随机标定的红外目标点的识别效果不好。提出一种基于Harris角点检测的遥感图像中微小红外目标的分类定位识别算法。构建遥感图像的红外目标数据采集模型,对图像进行角点特征提取预处理,采用Harris角点检测算法实现对红外目标微小特征点的信息标定,实现对其准确分类定位。仿真实验表明,采用该算法进行微小红外目标的分类定位识别,具有较高的准确性,对红外目标的特征提取和定位识别效果较好,在远程目标探测和遥感监测等领域具有较高的应用价值。

关键词：遥感图像红外目标角点检测算法

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Confidence-driven infrared target detection

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infrared PHYSICS & technology 2014年 66卷 78-83页

作者： Zhang, Zhiguo Liu, Liman Tao, Wenbing Tang, Yuanyan Huazhong Univ Sci & Technol Sch Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Natl Key Lab Sci & Technol Multispectral Informat Wuhan 430074 Peoples R China South Cent Univ Nationalities Sch Biomed Engn Wuhan 430074 Peoples R China Cent China Normal Univ Coll Phys Sci & Technol Wuhan 430073 Peoples R China Univ Macau Dept Comp & Informat Sci Macao Peoples R China

The confidence of target detection can be used to evaluate the reliability and risk level of the detected targets and can effective help to exclude the false alarms, but very little investigation was involved in the past. In this letter, a confidence-driven infrared target detection method is proposed. We develop three confidence evaluating methods: (1) the median classification confidence of the cascade classifier;(2) the context confidence based on the number and the confidence of the merged detection rectangles around the detected target;and (3) the contrast confidence based on the difference between the detected target distribution and the around background distribution. The three confidences are combined to form the final confidence of the detected targets. We then use the confidence to refine the localization of the targets. The evaluation using real infrared images demonstrates the good performance of the proposed confidence-driven infrared detection algorithm on both undetected error and false alarm. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Confidence evaluation target detection infrared Localization False alarm

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A Photogrammetric Approach for Real-time 3D Localization and Tracking of Pedestrians in Monocular infrared Imagery 10

A Photogrammetric Approach for Real-time 3D Localization and...

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Conference on Optics and Photonics for Counterterrorism, Crime Fighting, and Defence X and Optical Materials and Biomaterials in Security and Defence Systems technology XI

作者： Kundegorski, Mikolaj E. Breckon, Toby P. Univ Durham Sch Engn & Comp Sci Durham DH1 3HP England

ISBN: (纸本)9781628413168

target tracking within conventional video imagery poses a significant challenge that is increasingly being addressed via complex algorithmic solutions. The complexity of this problem can be fundamentally attributed to the ambiguity associated with actual 3D scene position of a given tracked object in relation to its observed position in 2D image space. We propose an approach that challenges the current trend in complex tracking solutions by addressing this fundamental ambiguity head-on. In contrast to prior work in the field, we leverage the key advantages of thermal-band infrared (IR) imagery for the pedestrian localization to show that robust localization and foreground target separation, afforded via such imagery, facilities accurate 3D position estimation to within the error bounds of conventional Global Position System (GPS) positioning. This work investigates the accuracy of classical photogrammetry, within the context of current target detection and classification techniques, as a means of recovering the true 3D position of pedestrian targets within the scene. Based on photogrammetric estimation of target position, we then illustrate the efficiency of regular Kalman filter based tracking operating on actual 3D pedestrian scene trajectories. We present both a statistical and experimental analysis of the associated errors of this approach in addition to real-time 3D pedestrian tracking using monocular infrared (IR) imagery from a thermal-band camera.

关键词： thermal target tracking temporal filtering intelligent target reporting thermal imaging pedestrian detection people detection sensor networks temporal fusion passive target positioning 3D pedestrian localization

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红外偏振成像探测技术进展

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红外与激光工程 2014年第10期43卷 3175-3182页

作者：王霞夏润秋金伟其刘敬梁建安北京理工大学光电学院光电成像技术与系统教育部重点实验室北京100081

不同物体不同状态存在明显的红外偏振差异,可以构成目标探测信息。简述了利用红外偏振成像技术进行目标探测的物理本质,重点阐述了偏振双向反射分布函数原理,列举了红外偏振成像探测模型,介绍了红外偏振成像技术的应用优势,归纳总结了... 详细信息

不同物体不同状态存在明显的红外偏振差异,可以构成目标探测信息。简述了利用红外偏振成像技术进行目标探测的物理本质,重点阐述了偏振双向反射分布函数原理,列举了红外偏振成像探测模型,介绍了红外偏振成像技术的应用优势,归纳总结了偏振成像系统结构分类及其特点,叙述了红外偏振成像技术在目标探测与识别领域的进展,详细叙述了红外偏振成像技术的理论、实验基础研究和在目标探测中的应用。最后,总结分析了中/长波红外偏振成像技术特点,并对发展国内红外偏振成像技术提出了建议。

关键词：红外偏振成像目标探测偏振双向反射分布函数偏振特性

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A Comparison of Real and Simulated Airborne Multisensor Imagery

A Comparison of Real and Simulated Airborne Multisensor Imag...

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20th SPIE Conference on Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery

作者： Bloechl, Kevin De Angelis, Chris Gartley, Michael Kerekes, John Nance, C. Eric Rochester Inst Technol Chester F Carlson Ctr Imaging Sci Digital Imaging & Remote Sensing Lab 54 Lomb Mem Dr Rochester NY 14623 USA Raytheon Intelligence Informat & Serv Garland TX USA

ISBN: (纸本)9781628410259

This paper presents a methodology and results for the comparison of simulated imagery to real imagery acquired with multiple sensors hosted on an airborne platform. The dataset includes aerial multi- and hyperspectral imagery with spatial resolutions of one meter or less. The multispectral imagery includes data from an airborne sensor with three-band visible color and calibrated radiance imagery in the long-, mid-, and short-wave infrared. The airborne hyperspectral imagery includes 360 bands of calibrated radiance and reflectance data spanning 400 to 2450 nm in wavelength. Collected in September 2012, the imagery is of a park in Avon, NY, and includes a dirt track and areas of grass, gravel, forest, and agricultural fields. A number of artificial targets were deployed in the scene prior to collection for purposes of target detection, subpixel detection, spectral unmixing, and 3D object recognition. A synthetic reconstruction of the collection site was created in DIRSIG, an image generation and modeling tool developed by the Rochester Institute of technology, based on ground-measured reflectance data, ground photography, and previous airborne imagery. Simulated airborne images were generated using the scene model, time of observation, estimates of the atmospheric conditions, and approximations of the sensor characteristics. The paper provides a comparison between the empirical and simulated images, including a comparison of achieved performance for classification, detection and unmixing applications. It was found that several differences exist due to the way the image is generated, including finite sampling and incomplete knowledge of the scene, atmospheric conditions and sensor characteristics. The lessons learned from this effort can be used in constructing future simulated scenes and further comparisons between real and simulated imagery.

关键词： Scene modeling hyperspectral multispectral target detection unmixing classification sensor performance

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