Learning Surveillance Tracking Models for the Self-Calibrated Ground Plane

J. Renno; P. Remagnino; G. A. Jones

首页> 外文期刊>Acta Automatica Sinica >Learning Surveillance Tracking Models for the Self-Calibrated Ground Plane

【24h】

Learning Surveillance Tracking Models for the Self-Calibrated Ground Plane

机译：自校准地面飞机的学习监视跟踪模型

获取原文

获取原文并翻译 | 示例

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

文献代查 >>

页面导航

摘要
著录项
相似文献
相关主题

摘要

We propose a novel method for combining information streamed by a multi-sensor system for visual surveillance. Information fusion occurs in two phases during which all cameras are calibrated with respect to independent global Cartesian reference frames (set on the ground plane) and then all frames are registered into a single coordinate system. The development of automatic calibration and registering of visual data is crucial in visual surveillance applications because it makes easier to install the monitoring infrastructure and, consequently, to develop more accessible Visual Surveillance tools for the public domain. Machine learning techniques are believed to offer the best mathematical tools to handle the uncertainty and incomplete nature of surveillance data.

机译：我们提出了一种新颖的方法，用于组合由多传感器系统流传输的信息进行视觉监视。信息融合分两个阶段进行，在此阶段中，将所有摄像机相对于独立的全局笛卡尔参考坐标系（在地平面上设置）进行校准，然后将所有坐标系注册到单个坐标系中。视觉数据的自动校准和注册的开发在视觉监视应用中至关重要，因为它可以更轻松地安装监视基础结构，从而为公共领域开发更易于访问的视觉监视工具。据信，机器学习技术可提供最佳的数学工具来处理监视数据的不确定性和不完整性。

著录项

来源
《Acta Automatica Sinica》 |2003年第3期|p.381-392|共12页
作者
J. Renno; P. Remagnino; G. A. Jones;
展开▼
作者单位

Digital Imaging Research Centre, Kingston University, Kingston, U. K.;

展开▼
收录信息
原文格式 PDF
正文语种 eng
中图分类自动化技术、计算机技术;
关键词
visual surveillance; machine learning; data fusion; camera calibration;

机译：视觉监控;机器学习;数据融合;相机校准;

相似文献

外文文献
中文文献
专利

1. Multi-object Detection and Tracking (MODT) Machine Learning Model for Real-Time Video Surveillance Systems [J] . Elhoseny M. Circuits, systems, and signal processing . 2020,第2期

机译：用于实时视频监控系统的多对象检测和跟踪（MODT）机器学习模型
2. Air-Ground Surveillance Sensor Network based on edge computing for target tracking [J] . Deng Xiaoheng, Liu Yajun, Zhu Congxu, Computer Communications . 2021,第Jana期

机译：基于边缘计算的空气地监控传感器网络进行目标跟踪
3. Moving Camera-Based Object Tracking Using Adaptive Ground Plane Estimation and Constrained Multiple Kernels [J] . Tao Liu, Yong Liu Journal of advanced transportation . 2021,第a期

机译：使用自适应地平面估计和约束多个内核移动基于相机的对象跟踪
4. Towards plug-and-play visual surveillance: learning tracking models [C] . Renno J., Orwell J., Jones G.A. Image Processing. 2002. Proceedings. 2002 International Conference on . 2002

机译：走向即插即用的视觉监控：学习跟踪模型
5. Path Tracking of Ground Vehicles Using Pure Tracking, Stanley and Ribbon Models Through Ros Gazebo Simulation and Comparison [D] . Li, Yubo. 2021

机译：通过ROS凉坡模拟和比较，使用纯跟踪，斯坦利和丝带模型的地面车辆的路径跟踪
6. Aortic and mitral flow quantification using dynamic valve tracking and machine learning: Prospective study assessing static and dynamic plane repeatability variability and agreement [O] . Julio Garcia, Kailey Beckie, Ali F Hassanabad, 2021

机译：使用动态阀门跟踪和机器学习的主动脉和二尖瓣流量：评估静态和动态平面可重复性可变性和协议的前瞻性研究
7. Learning surveillance tracking models for the self-calibrated ground plane [O] . Renno J., Orwell J., JONES G.A. 2002

机译：学习自校准地平面的监视跟踪模型
8. Moving Ground Plane Wind Tunnel Tests on Several Tracked Air Cushion Vehicle (Tacv) Models [R] . 1969

机译：几种履带式气垫车（Tacv）模型的移动地平面风洞试验

Learning Surveillance Tracking Models for the Self-Calibrated Ground Plane

摘要

著录项

相似文献

相关主题

期刊订阅