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Sensor planning method for visual tracking in 3D camera networks 被引量:1
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作者 Anlong Ming Xin Chen 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2014年第6期1107-1116,共10页
Most sensors or cameras discussed in the sensor network community are usually 3D homogeneous, even though their2 D coverage areas in the ground plane are heterogeneous. Meanwhile, observed objects of camera networks a... Most sensors or cameras discussed in the sensor network community are usually 3D homogeneous, even though their2 D coverage areas in the ground plane are heterogeneous. Meanwhile, observed objects of camera networks are usually simplified as 2D points in previous literature. However in actual application scenes, not only cameras are always heterogeneous with different height and action radiuses, but also the observed objects are with 3D features(i.e., height). This paper presents a sensor planning formulation addressing the efficiency enhancement of visual tracking in 3D heterogeneous camera networks that track and detect people traversing a region. The problem of sensor planning consists of three issues:(i) how to model the 3D heterogeneous cameras;(ii) how to rank the visibility, which ensures that the object of interest is visible in a camera's field of view;(iii) how to reconfigure the 3D viewing orientations of the cameras. This paper studies the geometric properties of 3D heterogeneous camera networks and addresses an evaluation formulation to rank the visibility of observed objects. Then a sensor planning method is proposed to improve the efficiency of visual tracking. Finally, the numerical results show that the proposed method can improve the tracking performance of the system compared to the conventional strategies. 展开更多
关键词 camera model sensor planning camera network visual tracking
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A Skeletal Camera Network for Close-range Images with a Data Driven Approach in Analyzing Stereo Configuration 被引量:3
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作者 Zhihua XU Lingling QU 《Journal of Geodesy and Geoinformation Science》 2022年第4期23-37,共15页
Structure-from-Motion(SfM)techniques have been widely used for 3D geometry reconstruction from multi-view images.Nevertheless,the efficiency and quality of the reconstructed geometry depends on multiple factors,i.e.,t... Structure-from-Motion(SfM)techniques have been widely used for 3D geometry reconstruction from multi-view images.Nevertheless,the efficiency and quality of the reconstructed geometry depends on multiple factors,i.e.,the base-height ratio,intersection angle,overlap,and ground control points,etc.,which are rarely quantified in real-world applications.To answer this question,in this paper,we take a data-driven approach by analyzing hundreds of terrestrial stereo image configurations through a typical SfM algorithm.Two main meta-parameters with respect to base-height ratio and intersection angle are analyzed.Following the results,we propose a Skeletal Camera Network(SCN)and embed it into the SfM to lead to a novel SfM scheme called SCN-SfM,which limits tie-point matching to the remaining connected image pairs in SCN.The proposed method was applied in three terrestrial datasets.Experimental results have demonstrated the effectiveness of the proposed SCN-SfM to achieve 3D geometry with higher accuracy and fast time efficiency compared to the typical SfM method,whereas the completeness of the geometry is comparable. 展开更多
关键词 3D geometry reconstruction geometric factors skeletal camera network STRUCTURE-FROM-MOTION tie-point matching terrestrial stereo images
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Web-Based Object Tracking Using Collaborated Camera Network
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作者 Abul K. M. Azad Mohammed Misbahuddin 《Advances in Internet of Things》 2018年第2期13-25,共13页
The paper presents a web based vision system using a networked IP camera for tracking objects of interest. Three critical issues are addressed in this paper. First is the detection of moving objects in the foreground;... The paper presents a web based vision system using a networked IP camera for tracking objects of interest. Three critical issues are addressed in this paper. First is the detection of moving objects in the foreground;second is the control of pan-tilt-zoom (PTZ) IP cameras based on object location;and third is the collaboration of multiple cameras over the network to track objects of interests independently. The developed system utilized a network of PTZ cameras along with a number of software tools for this implementation. The system was able to track a single and multiple objects successfully. The difficulties in the detection of moving objects are also analyzed while multiple cameras are collaborating over a network utilizing PTZ cameras. 展开更多
关键词 Internet Protocol camera networkED camera VISION TRACKING TRACKING HANDOVER Image Processing Collaborated TRACKING
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An Efficient Surveillance Data Management Scheme for Large-Scale Smart Camera Networks
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作者 Soomi Yang 《通讯和计算机(中英文版)》 2012年第11期1263-1268,共6页
关键词 智能摄像机 监测数据 数据管理 网络 监控系统 智能相机 多媒体数据 上下文信息
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Automatic Service Discovery of IP Cameras over Wide Area Networks with NAT Traversal
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作者 Chien-Min Ou Wei-De Wu 《Advances in Internet of Things》 2012年第2期23-36,共14页
A novel framework for remote service discovery and access of IP cameras with Network address Translation (NAT) traversal is presented in this paper. The proposed protocol, termed STDP (Service Trader Discovery Protoco... A novel framework for remote service discovery and access of IP cameras with Network address Translation (NAT) traversal is presented in this paper. The proposed protocol, termed STDP (Service Trader Discovery Protocol), is a hybrid combination of Zeroconf and SIP (Session Initial Protocol). The Zeroconf is adopted for the discovery and/or publication of local services;whereas, the SIP is used for the delivery of local services to the remote nodes. In addition, both the SIP-ALG (Application Layer Gateway) and UPnP (Universal Plug and Play)-IGD (Internet Gateway Device) protocols are used for NAT traversal. The proposed framework is well-suited for high mobility applications where the fast deployment and low administration efforts of IP cameras are desired. 展开更多
关键词 IP camera (IP CAM) network ADDRESS TRANSLATION (NAT) SESSION Initial Protocol (SIP)
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Modeling Camera Image Formation Using a Feedforward Neural Network
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作者 Yongtae Do 《Open Journal of Applied Sciences》 2013年第1期75-78,共4页
One fundamental problem in computer vision and image processing is modeling the image formation of a camera, i.e., mapping a point in three-dimensional space to its projected position on the camera’s image plane. If ... One fundamental problem in computer vision and image processing is modeling the image formation of a camera, i.e., mapping a point in three-dimensional space to its projected position on the camera’s image plane. If the relationship between the space and the image plane is assumed to be linear, the relationship can be expressed in terms of a transfor-mation matrix and the matrix is often identified by regression. In this paper, we show that the space-to-image relation-ship in a camera can be modeled by a simple neural network. Unlike most other cases employing neural networks, the structure of the network is optimized so as for each link between neurons to have a physical meaning. This makes it possible to effectively initialize link weights and quickly train the network. 展开更多
关键词 camera Model camera CALIBRATION IMAGE FORMATION NEURAL network
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基于卷积网络和深度相机的飞机牵引车防碰撞安全检测系统设计
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作者 孙丰源 张军 +3 位作者 黄明辉 向富尧 王一旋 刘宇新 《科学技术与工程》 北大核心 2026年第4期1728-1734,共7页
针对飞机牵引作业时的视野盲区大,存在安全隐患的问题,提出以深度相机与卷积神经网络(convolutional neural network,CNN)模型相融合的防碰撞检测方法。采用卷积网络实现环境目标的自动识别,利用深度相机获取目标距离信息,二者联合使用... 针对飞机牵引作业时的视野盲区大,存在安全隐患的问题,提出以深度相机与卷积神经网络(convolutional neural network,CNN)模型相融合的防碰撞检测方法。采用卷积网络实现环境目标的自动识别,利用深度相机获取目标距离信息,二者联合使用实现牵引过程障碍物的定位。将训练的卷积网络模型和ZED2i双目相机部署再飞机牵引车上,通过CAN总线进行通信,在试验场开展了避障实验。结果表明:构建的卷积网络模型识别准确率达到0.911,召回率达到0.803;在10 m测距范围内,测距误差在0.3 m以内,能够为飞机牵引车在牵引作业时的防碰撞安全检测提供技术参考。 展开更多
关键词 飞机牵引车 防碰撞检测 深度相机 卷积神经网络(CNN) 目标定位
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基于视觉引导的机械臂控制算法设计
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作者 马振波 周波 《工业控制计算机》 2026年第2期75-76,79,共3页
在机械臂与视觉融合领域,快速且稳健的目标检测与识别对机械臂控制至关重要。结合双目摄像头图像处理技术与机械臂控制技术,旨在构建一个高效的人机交互系统。首先,通过手眼标定获取了相机坐标系与机械臂基坐标系之间的转换关系。随后,... 在机械臂与视觉融合领域,快速且稳健的目标检测与识别对机械臂控制至关重要。结合双目摄像头图像处理技术与机械臂控制技术,旨在构建一个高效的人机交互系统。首先,通过手眼标定获取了相机坐标系与机械臂基坐标系之间的转换关系。随后,采用SSD神经网络并融合多尺度特征技术,实现了高效的手势识别与手部关键点检测,显著提高了检测精度与处理速度。最后,利用串口通信将手势识别信息传递给机械臂控制系统,从而实现精确的机械臂运动控制。实验结果表明,该方法相较于传统的手势识别技术在性能上具有明显优势,为机械臂在视觉引导下执行抓取任务提供了技术支持。 展开更多
关键词 手势识别 双目相机 机械臂控制 神经网络
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相机源识别方法中的自适应注意力密集网络结构研究
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作者 吴昊璇 文志强 《湖南工业大学学报》 2026年第1期85-91,共7页
为了提高深度学习模型在相机源识别领域的识别精度,设计了自适应注意力密集网络结构,并提出了自适应权重注意力方法。设计的网络结构包括预处理结构、密集连接结构、注意力结构、正则化结构4部分。注意力机制结构中采用自适应权重注意... 为了提高深度学习模型在相机源识别领域的识别精度,设计了自适应注意力密集网络结构,并提出了自适应权重注意力方法。设计的网络结构包括预处理结构、密集连接结构、注意力结构、正则化结构4部分。注意力机制结构中采用自适应权重注意力方法,通过引入自适应权重因子,实现参数自适应优化,以便获取适应不同数据特点的最优注意力权重,提升模型特征学习和特征表达能力。并在两个经典数据集上进行了对比实验和消融实验。在对比实验中,与3个经典网络进行了比较,实验结果表明设计网络的识别性能在两个数据集上分别比其他3个网络至少提高了5.547%,9.58%;消融实验结果表明,提出方法的识别性能在两个数据集上分别比其他消融方法至少提高了2.107%,4.732%。 展开更多
关键词 相机源识别 注意力机制 自适应权重 卷积神经网络
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基于Smart Camera的目标识别和加密传输 被引量:1
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作者 陈圣熙 陆盛浩 《电视技术》 北大核心 2011年第23期149-152,160,共5页
提出用一种以DSP为硬件核心的智能数字网络摄像机Smart Camera取代传统摄像机。它能够在对监控图像进行目标识别及其信息提取的同时,将特征信息经过RSA加密后通过网络传输,并可根据后方PC机的远程控制,给出不同的报警需求,实现了摄像机... 提出用一种以DSP为硬件核心的智能数字网络摄像机Smart Camera取代传统摄像机。它能够在对监控图像进行目标识别及其信息提取的同时,将特征信息经过RSA加密后通过网络传输,并可根据后方PC机的远程控制,给出不同的报警需求,实现了摄像机的智能化、数字化、网络化以及多用途。 展开更多
关键词 SMART camera 目标识别 RSA 网络视频监控
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融合多光谱成像与卷积神经网络的储粮害虫智能识别方法
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作者 苏靖 《粮食与饲料工业》 2026年第1期52-58,共7页
当前储粮害虫识别技术因传统可见光成像难以捕捉害虫与粮粒间的光谱差异,导致多尺度虫态特征割裂;同时,基于单一尺度特征的识别模型易受光照变化、粮粒遮挡等复杂仓储环境干扰,造成识别精度低、漏检与误检严重的问题。为此,研究提出一... 当前储粮害虫识别技术因传统可见光成像难以捕捉害虫与粮粒间的光谱差异,导致多尺度虫态特征割裂;同时,基于单一尺度特征的识别模型易受光照变化、粮粒遮挡等复杂仓储环境干扰,造成识别精度低、漏检与误检严重的问题。为此,研究提出一种融合多光谱成像与改进YOLOv4卷积神经网络的储粮害虫智能识别方法。通过构建涵盖图像输入、图像处理与图像输出组件的多光谱成像采集框架,利用多光谱相机获取659 nm和955 nm关键波段图像,并经过黑白板校正、多光谱配准及最小噪声分离变换进行预处理;将预处理数据输入改进YOLOv4模型,依托CSPDarknet53逐层提取害虫层级特征,采用双向特征金字塔网络替代原PANet结构实现跨尺度自适应融合,通过多任务损失函数协同优化定位与分类。在自建储粮害虫多光谱数据集上的实验结果表明,多光谱成像在659 nm和955 nm关键波段具有显著的光谱区分性;经最小噪声分离降维后,多光谱特征的平均J-M距离达到0.89,与识别模型高度适配。改进后的模型能够实现储粮害虫的精准识别,无漏检与误判现象。 展开更多
关键词 多光谱成像 卷积神经网络 储粮害虫识别 YOLOv4 多光谱相机 特征金字塔
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Energy Efficient Content Based Image Retrieval in Sensor Networks
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作者 Qurban A. Memon Hend Alqamzi 《International Journal of Communications, Network and System Sciences》 2012年第7期405-415,共11页
The presence of increased memory and computational power in imaging sensor networks attracts researchers to exploit image processing algorithms on distributed memory and computational power. In this paper, a typical p... The presence of increased memory and computational power in imaging sensor networks attracts researchers to exploit image processing algorithms on distributed memory and computational power. In this paper, a typical perimeter is investigated with a number of sensors placed to form an image sensor network for the purpose of content based distributed image search. Image search algorithm is used to enable distributed content based image search within each sensor node. The energy model is presented to calculate energy efficiency for various cases of image search and transmission. The simulations are carried out based on consideration of continuous monitoring or event driven activity on the perimeter. The simulation setups consider distributed image processing on sensor nodes and results show that energy saving is significant if search algorithms are embedded in image sensor nodes and image processing is distributed across sensor nodes. The tradeoff between sensor life time, distributed image search and network deployed cost is also investigated. 展开更多
关键词 IMAGE SENSOR networkS IMAGE Identification in SENSOR network camera SENSOR networkS Distributed IMAGE SEARCH
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An Automatic System of Vehicle Number-Plate Recognition Based on Neural Networks 被引量:2
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作者 Wei Wu Dept. of Road and Traffic Engineering, Changsha Communications University, 410076, P. R. China Huang Xinhan, Wang Min & Song Yexin Dept. of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, P. R. China 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2001年第2期63-72,共10页
This paper presents an automatic system of vehicle number-plate recognition based on neural networks. In this system, location of number-plate and recognition of characters in number-plate can be automatically complet... This paper presents an automatic system of vehicle number-plate recognition based on neural networks. In this system, location of number-plate and recognition of characters in number-plate can be automatically completed. Pixel colors of Number-plate area are classified using neural network, then color features are extracted by analyzing scanning lines of the cross-section of number-plate. It takes full use of number-plate color features to locate number-plate. Characters in number-plate can be effectively recognized using the neural networks. Experimental results show that the correct rate of number-plate location is close to 100%, and the time of number-plate location is less than 1 second. Moreover, recognition rate of characters is improved due to the known number-plate type. It is also observed that this system is not sensitive to variations of weather, illumination and vehicle speed. In addition, and also the size of number-plate need not to be known in prior. This system is of crucial significance to apply and spread the automatic system of vehicle number-plate recognition. 展开更多
关键词 cameras Charge coupled devices Feature extraction Neural networks VEHICLES
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基于单目相机的仓储托盘视觉检测研究
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作者 张彦 曹磊 +1 位作者 肖献强 王家恩 《机械设计与制造》 北大核心 2025年第12期352-356,共5页
针对托盘搬运机器人(Automatic Guided Vehicle,AGV)在复杂环境下对仓储托盘存在错误感知、过大的定位误差等问题,提出了基于单目相机的仓储托盘视觉检测方法。用相机实时采集场景图像,以轻量级SSD神经网络进行全局图像识别,分割出相机... 针对托盘搬运机器人(Automatic Guided Vehicle,AGV)在复杂环境下对仓储托盘存在错误感知、过大的定位误差等问题,提出了基于单目相机的仓储托盘视觉检测方法。用相机实时采集场景图像,以轻量级SSD神经网络进行全局图像识别,分割出相机视野下目标托盘的感性区域,在感性区域内进行图像处理、线段拟合,并在此基础上,设计了仓储托盘的特征提取算法,通过相机内外参标定、坐标系转换获取世界坐标系下托盘的三维位姿。测试结果表明仓储托盘的视觉检测具有较高的识别率和精度,有效检测率达到90%,定位精度达到横向9mm、纵向10mm,为AGV在智能仓储及无人化工厂中对托盘的视觉检测研究提供了技术支撑。 展开更多
关键词 单目相机 神经网络 视觉检测 特征提取
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基于RGB相机的无标志物TMS机器人辅助定位方法
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作者 程强 赵帅 +3 位作者 郝小龙 刘杰 许静静 李世俊 《北京工业大学学报》 北大核心 2025年第8期908-917,共10页
经颅磁刺激(transcranial magnetic stimulation, TMS)是一种神经调制方法,临床中凭借医生经验手动确定TMS线圈摆放位姿,导致线圈摆放位置和姿态不准确且重复定位精度差。针对上述问题,提出一种TMS线圈机器人辅助定位系统,使用RGB相机... 经颅磁刺激(transcranial magnetic stimulation, TMS)是一种神经调制方法,临床中凭借医生经验手动确定TMS线圈摆放位姿,导致线圈摆放位置和姿态不准确且重复定位精度差。针对上述问题,提出一种TMS线圈机器人辅助定位系统,使用RGB相机替代导航系统中双目红外相机,采用一种基于神经网络的无标志物TMS线圈机器人辅助定位方法。搭建神经网络实现相机空间线圈姿态到操作臂空间关节角度的映射,并通过仿真数据训练验证了该神经网络架构适用于TMS线圈位姿摆放问题。随后,通过实验验证了该方法的可行性,同时表明训练的神经网络针对TMS线圈定位任务具有良好的泛化能力。最后,在笛卡儿空间的位姿验证结果显示TMS线圈三维位置平均误差为2.16 mm,总体姿态误差为0.055 rad,使用RGB相机的TMS线圈机器人辅助定位系统在精度上达到了与其他使用双目红外相机的科研或商用系统相同的水平,满足TMS临床治疗要求,具备临床应用的可行性。 展开更多
关键词 经颅磁刺激(transcranial magnetic stimulation TMS) 机器人辅助TMS系统 RGB相机 神经网络 位姿估计 手眼标定
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In-Motes EYE: A Real Time Application for Automobiles in Wireless Sensor Networks
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作者 Dimitrios Georgoulas Keith Blow 《Wireless Sensor Network》 2011年第5期158-166,共9页
Wireless sensor networks have been identified as one of the key technologies for the 21st century. In order to overcome their limitations such as fault tolerance and conservation of energy, we propose a middleware sol... Wireless sensor networks have been identified as one of the key technologies for the 21st century. In order to overcome their limitations such as fault tolerance and conservation of energy, we propose a middleware solution, In-Motes. In-Motes stands as a fault tolerant platform for deploying and monitoring applications in real time offers a number of possibilities for the end user giving him in parallel the freedom to experiment with various parameters, in an effort the deployed applications to run in an energy efficient manner inside the network. The proposed scheme is evaluated through the In-Motes EYE application, aiming to test its merits under real time conditions. In-Motes EYE application which is an agent based real time In-Motes application developed for sensing acceleration variations in an environment. The application was tested in a prototype area, road alike, for a period of four months. 展开更多
关键词 Wireless Sensor networks MIDDLEWARE Mobile AGENTS In-Motes ACCELERATION Measurements TRAFFIC cameras
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基于自适应辨识技术的高空接触网静/动态数据测量
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作者 欧志新 郁明 《福建技术师范学院学报》 2025年第5期1-11,94,共12页
接触网系统是轨道交通和高速铁路电力列车主要的供电设备,稳定电流传输和高精度的数据检测是安全重要基础。目前对高空接触网数据测量主要有静态和动态两种检测方式。首先,文中分析传统的接触网高空测量设备,包括摄像相机图像成像、超... 接触网系统是轨道交通和高速铁路电力列车主要的供电设备,稳定电流传输和高精度的数据检测是安全重要基础。目前对高空接触网数据测量主要有静态和动态两种检测方式。首先,文中分析传统的接触网高空测量设备,包括摄像相机图像成像、超声波和激光测距方式。其次,建立数据管理和处理软件,发现数据存在归类困难、波动辨识度低、自动区分误差数据精准度低等缺点。最后,通过实验室模拟计算,将基于自适应算法的模糊辨识理论引入数据管理系统软件,建立接触网辨识模型,现场测量数据自主修正误差率提高约17%,测量数据响应时间提升20%,具有较强的实践应用意义。 展开更多
关键词 接触网动静态数据 激光测距 摄像机图像采集 自适应算法 数据管理软件
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基于机器视觉技术的光学材料表面划痕检测
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作者 王迎敏 张小勇 《激光杂志》 北大核心 2025年第12期243-249,共7页
考虑光学材料表面划痕大小不一,增加划痕视觉检测难度,提出基于机器视觉技术的光学材料表面划痕检测方法。采集光学材料表面图像;使用傅里叶变换增强光学材料表面图像,增强图像输入深度卷积神经网络,由VGG-16网络构建光学材料表面划痕... 考虑光学材料表面划痕大小不一,增加划痕视觉检测难度,提出基于机器视觉技术的光学材料表面划痕检测方法。采集光学材料表面图像;使用傅里叶变换增强光学材料表面图像,增强图像输入深度卷积神经网络,由VGG-16网络构建光学材料表面划痕检测模型,卷积提取增强后光学材料表面图像的灰度特征,识别光学材料表面划痕图像;针对划痕图像,由最大内接圆直径替代法、骨架化算法完成光学材料表面划痕检测。实验结果显示:此方法的光学透镜材料表面划痕检测结果的像素准确率、平均交并比均大于0.95,与人工标注结果之间仅有0.01像素之差,具有较高的检测准确性。 展开更多
关键词 机器视觉技术 光学材料 表面图像 划痕检测 CCD相机 深度卷积神经网络
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数据集对基于卷积神经网络算法的编码孔径γ相机成像质量影响 被引量:1
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作者 许文瑞 宋玉收 +2 位作者 周春芝 侯英伟 刘辉兰 《核技术》 北大核心 2025年第4期62-70,共9页
卷积神经网络(Convolutional Neural Network,CNN)算法已被用于编码孔径γ相机的图像重建中,提升了对成像过程中随机噪声的抑制效果。对于CNN算法,数据集的设置将直接影响模型的性能,然而,现有研究尚缺乏对此问题的讨论。本文基于点源... 卷积神经网络(Convolutional Neural Network,CNN)算法已被用于编码孔径γ相机的图像重建中,提升了对成像过程中随机噪声的抑制效果。对于CNN算法,数据集的设置将直接影响模型的性能,然而,现有研究尚缺乏对此问题的讨论。本文基于点源成像过程开展研究,提出了一种基于蒙特卡罗模拟和线性随机组合的数据集生成方法,通过Geant4软件模拟编码孔径成像过程,并使用CNN算法完成图像重建。对点源定位时,^(57)Co数据集的训练模型对^(57)Co源定位的平均对比度信噪比(Contrast-to-Noise Ratio,CNR)为75.8,对^(60)Co定位的平均CNR为24.7;而使用^(137)Cs数据集的模型对二者定位的平均CNR分别为43.8与44.3;对视野内随机7个^(60)Co源重建时,模型重建的CNR为8.9,并且能够清晰识别放射源位置。因此,数据集的容量及特征性会直接影响到CNN模型的学习及泛化能力,在高能与多点源的条件下,选取合适的数据集,有助于提升对放射源成像的效果与准确性。 展开更多
关键词 编码孔径γ相机 卷积神经网络算法 PyTorch 蒙特卡罗模拟
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融合立体匹配算法与深度网络的机器人视觉三维建模动画研究
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作者 李鹏 王卉 《自动化与仪器仪表》 2025年第2期233-237,共5页
针对机器人的视觉三维建模动画方法低准确性与泛化性差的问题,研究提出了基于立体匹配算法的双目视觉同步定位与构图方法,并设计了融合立体匹配算法与深度网络的视觉三维建模动画方法。研究结果表明,研究方法在室外环境中平均交并比与... 针对机器人的视觉三维建模动画方法低准确性与泛化性差的问题,研究提出了基于立体匹配算法的双目视觉同步定位与构图方法,并设计了融合立体匹配算法与深度网络的视觉三维建模动画方法。研究结果表明,研究方法在室外环境中平均交并比与整体精度分别为0.764与0.876 3,在室内场景中的各指标分别对应0.895 3和0.901 7,与目前最主流的方法相比,研究方法的绝对平均误差与正向平均误差分别减少了85.06%与85.71%。在实际应用效果中,研究方法能精准分割与识别场景中的部件类别。上述结果说明,研究方法能实现机器人视觉三维动画建模的高精度与适用性,提升机器人对不同环境的感知能力,为机器人进行双目实时动画场景的建模提供参考。 展开更多
关键词 立体匹配算法 深度网络 机器人视觉 三维建模 双目立体相机
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