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Description: surendra背景更新算法
oepncv-surendra background update algorithm
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Size: 2048 |
Author: liuxiaojie |
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Description: 基于视频的surendra背景更新算法,基于opencv和vc++,能够实现-Video-based surendra background update algorithm, based on opencv and vc++, can be achieved
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Size: 1486848 |
Author: liuxiaojie |
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Description: 利用图像序列的灰度统计特性来提取背景图像,并利用Surendra背景更新算法根据每帧图像对背景进行更新已获得可靠的背景.然后,将当前帧与背景作差,并对差值图像进行适当处理,这样运动目标就能够被精确地提取出来.
-Using statistical properties of image sequences to extract the gray background image and background updating algorithm based on the use Surendra each frame to update the background has been a reliable background. Then, the difference between the current frame and background, and difference images properly, this moving target can be accurately extracted.
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Size: 136192 |
Author: 汪 |
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Description: 首先采用苏伦德拉方法检测目标,然后用RGB颜色识别人脸-surendra method detect trarget and recognize face
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Size: 1024 |
Author: zhaoxunjie |
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Description: 实现快速背景建模,使用的是SURENDRA方法-Fast background modeling, SURENDRA method
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Size: 1024 |
Author: 张学真 |
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Description: 提出了一种改进的surendra 运动目标检测算法,该算法可以自适应的调整背景更新速度.-An improved surendra moving target detection algorithm, the algorithm can adaptively adjust the background updating speed.
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Size: 336896 |
Author: 张子龙 |
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Description: 背景提取,迭代法(Surendra算法);即采用帧差的方法,一帧图像减去前一帧图像,即可以对比得到图像中变化(移动)的区域,扣除移动的区域,即得到不动的背景。采用多帧图像迭代的方法,得到更加准确的背景。-Background extraction, iterative method (Surendra algorithm) frame difference method is used, an image by subtracting the previous frame, which can receive the image contrast change (movement) of the area, less the area of movement, that is obtained immovable background. Multi-frame image iteration method, to be more accurate background.
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Size: 1024 |
Author: wangxing |
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Description: 实现surendra背景差分,并和帧间差分比较效果-Achieve surendra background difference, and the comparative effectiveness of inter-frame difference
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Size: 1848320 |
Author: 潘姣 |
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Description: surendre 滤波算法,用于背景融合,行人识别(surendra filtering algorithm)
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Size: 1466368 |
Author: paradroid
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Description: 基于surendra算法,代码环境matlab,用于运动目标检测(Moving target detection based on Surendra)
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Size: 1024 |
Author: 郑联合KAIFAWANG |
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