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Q. Zhou, J.K. Aggarwal. Tracking and Classifying Moving Objects from Video. 这篇文章另辟蹊径，利用“紧凑度值的变化、运动方向的变化”，区分人、人群、机动车。达到良好的分类效果。是运动目标分类领域的好文章。-Q. Zhou, JK Aggarwal. Tracking and Classifying Moving Objects from Video. This article open a new path, by us
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智能视频监控系统中运动目标检测与跟踪技术的研究及其DSP实现-Intelligent video surveillance system for detecting and tracking moving objects and its DSP technology to achieve
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Face detection algorithms are widely used in computer vision as they provide fast and reliable results depending on the application
domain. A multi view approach is here presented to detect frontal and profile pose of people face using Histogram of
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This IEEE paper helps for tracking and classification of motion detection.
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Research in motion analysis has evolved over the years as a
challenging field. Moving object detection and tracking is of
major interest in applications such as traffic monitoring,
military, medicine and biological sciences etc. In this a ne
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motion tracking to detect and track moving objects through a sequence of images
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近些年，由于射频技术发展迅猛，应答器有了新的说法和含义，又被叫做智能标签或标签。RFID电子电梯合格证的阅读器（读写器）通过天线与RFID电子标签进行无线通信，可以实现对标签识别码和内存数据的读出或写入操作。典型的阅读器包含有高频模块（发送器和接收器）、控制单元以及阅读器天线。RFID射频识别是一种非接触式的自动识别技术，它通过射频信号自动识别目标对象并获取相关数据，识别工作无需人工干预，可工作于各种恶劣环境。RFID技术可识别高速运动物体并可同时识别多个标签，操作快捷方便。RFID是一种简单的
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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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在道路交通管理中，为了获得车辆的运动数据，早期经常采用的是感应线圈等硬件测量的方法。而如果采用摄像头拍摄的道路视频，再用计算机软件处理的方法，则可以极大的增加方便性和灵活性。本文运动目标检测与跟踪研究如何让计算机从视频图像序列中获得物体运动数据。-Traffic management in order to obtain motion data of the vehicle, is a method often used early induction coil measurement hard
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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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Tracking moving objects in video sequence is an important
problem in computer vision, with applications several
fields, such as video surveillance and target tracking. Most
techniques reported in the literature use background subtraction
tech
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重点讨论了改进后的粒子滤波理论在复杂场景下运动物体跟踪问题。-It discusses the theoretical particle filter improved tracking of moving objects in a complex scene.
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一个最新的对于运动物体跟踪的研究，思路很清晰，值得借鉴-A recent study for tracking moving objects, ideas very clear, is worth learning
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This example shows how to perform automatic detection and motion-based
tracking of moving objects in a video a stationary camera.
Copyright 2012-2015 The MathWorks, Inc.
Detection of moving objects and motion-based tracking are im
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This example shows how to perform automatic detection and motion-based
tracking of moving objects in a video a stationary camera.
Copyright 2012-2015 The MathWorks, Inc.
Detection of moving objects and motion-based tracking are im
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视频中运动的目标的跟踪检测,检测各种视频运动中的目标。(Tracking detection of moving objects in video)
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