共查询到18条相似文献,搜索用时 125 毫秒
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本文采用二重对称帧间差分目标检测算法和基于压缩感知的目标跟踪算法,设计并实现了一种可适应动态复杂背景下的智能视频监控系统。基于目标检测该系统能提取本地视频文件中局部运动目标并进行视频压缩,减少回放、查看视频时间,可实时播放并处理本地或网络摄像头数据,也可根据光照变化动态调整二值化阀值,实现实时区域入侵检测与报警。基于目标跟踪本系统能在动态背景下对选定目标进行跟踪,可通过客户端手动控制监控云台跟踪,也可对入侵目标实现云台自主大角度追踪。实验表明,本系统能在日常复杂环境下对运动目标准确检测和大角度跟踪,在智能家居和移动安防领域有很好的实用性。 相似文献
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针对红外测距与超声波测距探测距离与真实距离差异大,刹车控制智能性不强的问题,设计并实现了基于单目视觉测距的车辆自动刹车辅助系统,系统硬件主要由图像采集模块、图像处理模块、以及电子制动模块组成;通过基于单目视觉测距算法实现软件编程,并在Matlab平台上完成测试,实验中车辆以35 km/h驶向障碍物,使在20~70 m的实际距离进行仿真测距,单目摄像头俯仰角测定在88°~90°之间,对前方实时车距进行测量,并通过与汽车电子控制单元之间的数据交换对车辆制动进行辅助控制;实验结果表明:在实测距离和系统介入距离均在70 m以内时,算法相对误差平均在2%左右,车辆停止地点距障碍物在4.5 m左右,说明系统满足车辆智能化辅助制动的实时性要求。 相似文献
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康轶譞刘宇王亚伟周立君郭城王怡恬 《应用光学》2023,(4):786-791
DETR(detection transformer)算法是一个基于Transformer的目标检测算法,具有检测速度快、检测效果好的优势。介绍了一种利用DETR算法及双目视觉原理对道路环境下的人、车、自行车、信号灯等目标进行构建的测量系统。分析了双目测距、相机标定、目标检测以及目标匹配的原理,并以此为基础构建了测量系统。采用目标检测算法检测视野中的目标,利用双目视觉原理对检测到的目标进行测距,同时分析了测量系统中测量误差的来源,并计算其对结果的影响。该算法在KITTI数据集及现实环境中进行测试,测量系统基线为45 cm,对15 m~80 m的指定目标检出率高于90.6%,测距误差小于5.8%,在RTX 2080Ti平台上能够实时运行。 相似文献
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运动目标检测是智能视频监控系统中的重要步骤和前提。提出了一种基于随机背景建模的非参数化建模算法,对场景中运动目标进行快速提取跟踪。在初始化阶段,从当前像素的邻域中随机抽取样本值作为背景模型;在模型更新阶段,引入了随机更新策略和背景传播机制,能够较好地抑制环境噪声;在后处理阶段,给出了一种基于积分图的前景滤波优化方法,进一步滤除噪声和填充前景空洞。实验结果表明,在复杂场景条件下,算法的目标检测性能明显优于其他几种同类算法,能够较好地抑制噪声干扰,具有较高的检测正确率。对于360288像素的测试视频,算法的计算速度高达120 f/s,完全可以满足实时应用。 相似文献
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针对摄像机与被检测目标同时运动时的目标检测问题,提出一种立体视觉与光流融合的运动目标检测算法。结合立体视觉技术设计了光流与自运动估计模型,运用车辆的运动信息和场景的深度信息估计因摄像机运动产生的自运动光流;采用多分辨率细化的Horn算法估计场景的混合光流;对混合光流和自运动光流进行差分运算,剔除背景中静态目标的运动干扰。经过一系列形态学滤波处理获得运动目标完整区域,依据光流的连通性对运动目标标号,并确定位置信息。以典型的交通场景为对象进行分析,实验结果表明该算法能有效地检测出动态背景下的运动目标。 相似文献
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Extracting foreground moving objects from video sequences is an important task and also a hot topic in computer vision and image processing. Segmentation results can be used in many object-based video applications such as object-based video coding, content-based video retrieval, intelligent video surveillance and video-based human–computer interaction. In this paper, we present a novel moving object detection method based on improved VIBE and graph cut method from monocular video sequences. Firstly, perform moving object detection for the current frame based on improved VIBE method to extract the background and foreground information; then obtain the clusters of foreground and background respectively using mean shift clustering on the background and foreground information; Third, initialize the S/T Network with corresponding image pixels as nodes (except S/T node); calculate the data and smoothness term of graph; finally, use max flow/minimum cut to segmentation S/T network to extract the motion objects. Experimental results on indoor and outdoor videos demonstrate the efficiency of our proposed method. 相似文献
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Aimed at the shortcomings of the traditional video monitoring system, human detection method in intelligent video monitoring system was researched. This paper proposed a human detection method based on motion object extraction and head–shoulder feature to complete human detection and statistics in video image sequences. Firstly, background subtraction based on adaptive threshold was used to extract foreground moving object information, then image erosion and image dilation were used to bypass the object shade and remove false object in order to optimize the results of motion object extraction. And finally, for realizing human moving object detection, we proposed the object discrimination algorithm based on human head–shoulder feature to complete human detection and statistics. Experimental results show that the method can successfully realize human detection and statistics. The method is highly accurate and has good real-time and extensive applications. The identification rate is 86% through human video sequences to test. This method can detect human automatically and provide the theoretical and technological base for object detection in the intelligent surveillance system. 相似文献
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Diange Yang 《Journal of sound and vibration》2011,330(11):2457-2469
In this paper, a new acoustic video camera system is developed and its calibration method is established. This system is built based on binocular vision and acoustical holography technology. With binocular vision method, the spatial distance between the microphone array and the moving vehicles is obtained, and the sound reconstruction plane can be established closely to the moving vehicle surface automatically. Then the sound video is regenerated closely to the moving vehicles accurately by acoustic holography method. With this system, the moving and stationary sound sources are treated differently and automatically, which makes the sound visualization of moving vehicles much quicker, more intuitively, and accurately. To verify this system, experiments for a stationary speaker and a non-stationary speaker are carried out. Further verification experiments for outdoor moving vehicle are also conducted. Successful video visualization results not only confirm the validity of the system but also suggest that this system can be a potential useful tool in vehicle's noise identification because it allows the users to find out the noise sources by the videos easily. We believe the newly developed system will be of great potential in moving vehicles' noise identification and control. 相似文献
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运动目标检测跟踪有关的算法及其基于PC平台的实现已经比较成熟,但实时性较差。将采集的彩色视频流分成灰度和彩色两个数据流,灰度视频用于目标检测,彩色视频流用于跟踪显示。以经典的帧间差分法和背景差分法为基础,根据现场可编程门阵列(FPGA)的特点及片外同步动态存储器的存取控制要求,对这两个算法用FPGA逻辑单元进行了设计和实现。对原始彩色视频流和转换后的灰度视频流的存取使用乒乓操作,在滤波和形态学处理时使用了并行的流水线操作,极大地提高了算法的实时处理能力。在FPGA开发板上构建了一个彩色视频图像中运动目标检测跟踪系统,对系统性能进行了测试。实验结果表明,系统可在多种分辨率和帧率下进行运动目标进行实时检测跟踪;固定背景差分法对目标运动速度无限制,但当使用帧差法对快速运动目标进行有效的检测时,应使目标的帧差间距大于3.2像素。 相似文献