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学位论文；运动物体跟踪方法主要包括卡尔曼滤波，Mean-shift，Camshifi算法，粒子滤波器，Snake模型等；应用卡尔曼滤波方法设计了一套煤矿矿工出入自动监测系统；提出了一种新的基于高斯混合模型的颜色特征提取方法，该方法克服了现有的Camshift算法Continuousl y Adaptive eanshift中跟踪目标特征提取精确度低和计算复杂度高的缺陷-Dissertation moving object tracking methods include Kalman filt
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A paper on A Kalman Filter Based Visual Tracking Algorithm for an Object Moving in 3D
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the first introduction to Kalman Filter, methods that used to track moving object
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extracting background Bit-layer-A method of achieving background is presented
which detect the moving object with statistics from complex
scene. Compared with other methods of achieving image
background, this approach can achieve and update
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研究了目前运动对象检测与跟踪的一些常用方法,包括时域差分法、背景差分法、基于光流场的检测方法和卡尔曼滤波、特征光流法的跟踪方法,并对各种方法进行了比较,指出其优缺点及适用范围,并给出了时域差分及背景差分方法的实验结果-Currently some of the commonly used methods to study the detection and tracking of moving objects, including difference time domain method, b
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假设一物体围绕一圆周运动，角加速度是白噪声，观测噪声也是零均值的白噪声。编程使用卡尔曼滤波器实现运动物体的跟踪。-Suppose an object around a circular motion, the angular acceleration is white noise, measurement noise is zero mean white noise. Programming using a Kalman filter to achieve tracking moving obj
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This document represent the kalman filter which can track the moving object. it is proofed that this filter is optimal in the case of gaussianity.
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