Description: A multi-Kalman filtering approach for video tracking of human-delineated objects in cluttered environments is an latest PH.D graduation paper! it give to most needing people.-A multi-Kalman filtering approach for vid eo tracking of human-delineated objects in clu ttered environments is an latest PH.D. graduati on paper! it give needing to most people. Platform: |
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Description: 基于卡尔曼滤波器的物体追踪算法，很好用的，而且效率也很高-Kalman Filter-based object tracking algorithm, a very good use, but also high efficiency Platform: |
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Author:杜鲁燕 |
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Description: 卡尔曼滤波器是一个对动态系统的状态序列进行线性最小误差估计的算法，一般用于线性系统。一般在运动跟踪领域中摄像机相对于目标物体运动有时属于非线性系统，但由于在一般运动跟踪问题中图像采集时间间隔较短，可近似将单位时间内目标在图像中的运动看作匀速运动，采用卡尔曼滤波器可以实现对目标运动参数的估计。-Kalman filter is a state sequence of linear dynamic systems smallest error estimation algorithm for linear systems in general. Usually in the field of motion tracking camera motion with respect to the target object may belong to nonlinear systems, but in general due to motion tracking problems shorter image acquisition time interval, a unit of time can be approximated to the target motion in the image is regarded as uniform motion, Kalman filter can achieve the target motion parameter estimation. Platform: |
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Author:anly |
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Description: 本书以 Kalman 滤波器为主要介绍对象，包含基本原理、推导方 法及其在跟踪系统中的应用，同时配套 MATLAB 源程序。具体内容 包括 Kalman 滤波器、扩展 Kalman 滤波器、不敏 Kalman 滤波器及其 在 RFID 系统的跟踪应用研究。 本书凝练了作者二十余年来对 Kalman 滤波器基础理论及在目标 跟踪应用的研究成果，具体内容包括：根据目标运动特征进行自调整 参数的“自适应动力学模型”、不敏变换的性能分析、RFID 跟踪系 统的测量方程及其仿真平台等。 本书可作为自动化、电子信息、计算机应用、控制科学与工程、 信号处理、导航与制导等相关专业高年级本科生和研究生的教材，也 可供相关领域的工程技术人员和研究人员参考。(This book takes Kalman filter as the main introduction object, including the basic principle, derivation method and its application in the tracking system, and matching MATLAB source program. The specific contents include Kalman filter, extended Kalman filter, insensitive Kalman filter and its tracking application in RFID system. This book summarizes the author's research achievements on the basic theory of Kalman filter and its application in target tracking for more than twenty years.) Platform: |
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