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muanual.
his is a C implementation of background subtraction given a set of background frames as a training set.The background model is per-pixel RGB space Ga
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通过循环混合模型，失控过滤和阴影消除进行视频背景检测-Background subtraction in video using recursive mixture models, spatio-temporal filtering and shadow removal
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背景差和帧差法实现运动人体的跟踪，具有搞噪声和消除大部分阴影功能-Background subtraction and frame difference method to achieve the tracking of the movement of the human body to engage in noise and eliminate most of the shadow function
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OpenCV实现静止背景下运动目标的检测,通过背景差法检测出运动的目标。-OpenCV implementation static background moving target detection by background subtraction method to detect moving targets.
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一种基于背景减法和帧差的运动目标检测算法-Based on background subtraction and frame difference moving target detection algorithm
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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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高斯改进算法，背景减除法，方法很有效。可以参考-Gauss improved algorithm, background subtraction method, the method is very effective
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matlab GUI环境下的手势分割 采用肤色和背景差分 普通摄像头-gesture segmentation matlab GUI environment using color and background subtraction ordinary camera
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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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基于visual和opencv的运动目标检测，背景差分法-Opencv based on visual and moving target detection, background subtraction
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步态识别论文，对目标检测方法进行了分析，提出了在HSL颜色模型空间中，利用时间域中值滤波算法构建背景模型，采用背景减除法实现人体上肢和下肢关节点的检测，采用闽值分割、形态学滤波和颗粒去除操作对关节点的图像进行二值化处理，为后续相关特征的提取做好了准备。
-Gait identification papers, for target detection methods are analyzed, presented at the HSL color space model, using med
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运动目标检测是将位置发生改变的物体从背景中提取出来，它是运动目标跟踪、行为识别
和场景描述等技术的基础。运动目标检测的经典方法有光流法、帧间差分法和背景减除法。-Moving object detection is to change the position of the object extracted the background, it is a moving target tracking, behavior recognition
And underlying techno
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