智能监控系统的主动视觉与三维定位方法研究 -pg电子娱乐平台

密级专业硕士学位论文智能监控系统的主动视觉与三维定位方法研究校内指导教师姓名**称：龙永红教授校外指导教师姓名**称：武利冲高级工程师图像处理与机器视觉湖南工业大学二〇二三年五月二十二日researchactivevision3dpositioningbasedintelligentvideosurveillancezhulinathesissubmittedpartialsatisfactionelectronicinformationhunanuniversitytechnology88taishanwestroad,tianyuandistrictzhuzhouhunan412007,p.r.chinasupervisorprofessorlongyonghongapril,2023ii随着科学技术不断发展和工业智能化的快速推进，智能视频监控系统可以实现对工业生产过程的全面监测和分析，对企业的发展具有非常重要的意义。而动态目标的主动跟随与三维空间信息的提取一直是操作员工关注的重点，通常采用图像处理算法来检测动态目标并控制ptz（球型）摄像机进行实时跟随，但由于动态目标尺寸和背景的变化，导致检测精度无法满足实际需要。同时，在主动跟随过程中缺少对动态目标周围环境信息的提取，限制了视频监控系统在工业场景下的智能化应用。因此，论文主要从ptz摄像机模型建立与标定、主动跟随和三维定位三个方面进行研究，构建了一种精度高、速度快的动态目标主动跟随及三维坐标定位系统。该系统利用ptz摄像机可旋转、变焦特性对动态目标进行主动跟随，并结合双目立体视觉技术感知动态目标的三维空间信息。首先针对ptz摄像机成像模型在旋转、变焦过程中无法确定的问题，利用摄像机的光学成像原理，将ptz摄像机中动态参数偏航角（pan）、俯仰角（tilt）和焦距值（zoom）引入内外参数矩阵中，建立更加通用的ptz摄像机动态成像模型，最后采用棋盘标定法，实现摄像机内外参数的求解。针对目标检测和模糊控制理论来实现主动跟随时，极大依赖目标检测精度以及模糊控制算法精度低等问题，设计了基于ptz摄像机模型的动态目标主动跟随算法，即通过上述建立的动态成像模型来求解摄像机主动跟随所需的姿态角，并将该姿态角作为初始值。为了降低聚焦偏移现象和初次跟随姿态角计算误差的影响，后续采用自动对准算法来计算姿态角的二次增量值，实现动态目标在远距离也能精准地跟随动态目标。针对传统的特征点匹配在匹配精度和效率上无法满足实际工业现场三维定位要求，设计了一种基于极线约束下的ncc立体匹配算法，首先通过极线几何约束法将匹配区域固定在极线附近，极大的缩小匹配区域，后续采用ncc匹配算法来寻找相应特征点，最后通过摄像机投影矩阵法来求解三维空间点的坐标，实验分析可知，三维重建误差在0.29%左右，可满足实际工业现场定位要求。研究表明，基于ptz摄像机模型的动态目标主动跟随算法可快速、准确地跟随感兴趣目标，结合双目立体定位技术来提取动态目标周围环境的三维信息，可以实现视频监控系统的智能信息提取。关键词：视频监控系统，ptz摄像机，成像模型，主动跟随，双目视觉定位iiiabstractcontinuousdevelopmentrapidadvancementindustrialintelligence,intelligentvideosurveillancesystemscanachievecomprehensivemonitoringindustrialproductionprocesses,whichgreatsignificanceenterprises.however,activetrackingmovingtargetsthree-dimensionalspatialinformationhavealwaysbeenoperatorattention.usually,imageprocessingalgorithmsdetectmovingtargetscontrolptz(pan-tilt-zoom)camerasreal-timetracking,detectionaccuracyofteninsufficientduetargetsizebackground.additionally,environmentalinformationextractionaroundmovingtargetsduringactivetrackinglimitsintelligentapplicationvideosurveillancesystemsindustrialscenarios.therefore,ptzcameramodelestablishmentcalibration,activetracking,three-dimensionalpositioningfast-movingtargetactivetrackingthree-dimensionalcoordinatepositioningsystem.systemutilizesptzcamera'srotationzoomfeaturesactivelytrackmovingtargets,combinesbinocularstereovisiontechnologymovingtarget'sthree-dimensionalspatialinformation.firstly,ptzcameraimagingmodelbeingunabledeterminerotationzoomduringoperationopticalimagingprincipledynamicparametersyawangle(pan),pitchangle(tilt),focallength(zoom)externalparametermatricesmoreversatileptzcameradynamicimagingmodel.finally,chessboardcalibrationmethodexternalparametersactivetracking,whichheavilyreliestargetdetectionaccuracylowprecisionfuzzycontrolalgorithms,activetrackingalgorithmbasedptzcameramodeldynamicimagingmodelestablishedaboveattitudeanglerequiredcameraactivetrackinginitialvalue.focusoffsetinitialtracking attitude angle iv calculation error, automaticalignment algorithm second-order increments attitudeangle, enabling accurate tracking movingtargets even longdistances. three-dimensionalpositioning, traditional feature point matching matchingaccuracy meetpractical industrial site requirements. therefore, stereomatching algorithm based ncc(normalized cross correlation) under epipolarconstraint designed.firstly, matchingregion fixednear epipolarline using epipolargeometry constraint method, greatly reducing matchingarea. secondly, ncc matching algorithm findcorresponding feature points, cameraprojection matrix three-dimensionalspatial points. experimental analysis shows three-dimensionalreconstruction error about0.29%, which can meet practical industrial site positioning requirements. researchshows activetracking algorithm based ptzcamera model can quickly accuratelytrack movingtarget interest.combining binocular stereo positioning technology movingtarget's surrounding environmental three-dimensional information can realize intelligent information