Description: 采用块匹配法计算相邻两帧图像的运动矢量，并显示计算的矢量结果。其中使用了opencv里面的函数。需先安装和加入opencv的库。-Using the 3 step block matching algorithm to compute the motion vector of two consecutive frames. Platform: |
Size: 18996224 |
Author:wujin |
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Description: 基于opencv的帧率提升算法，可实现超低帧率（3~5帧）的视频插帧，速度达到应用标准，六边形搜索块匹配-Opencv based on frame rate to enhance algorithm can achieve ultra-low frame rate (3 to 5) of the video frame interpolation, speed of application standards, hexagon search block matching Platform: |
Size: 4096 |
Author:廖琦宇 |
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Description: 视频图像的人群密度检测，多种人群密度场景下人群计数算法：
算法功能:建立图像特征和图像人数的数学关系
算法输入:训练样本图像1,2…K
算法输出:模型估计参数 ，参考图像
算法流程：1)对训练样本图像进行分块处理(算法1.1)；
2)通过算法1.2，计算训练样本各个对应分块的ALBP特征归一化，再用K-means算法(可使用opencv等算法库实现，不再描述其算法)，将图像块分成k(k<K)类，获取k(k<K)个聚类中心，即为参考图像；
3)对分块的图像进行与参考图像进行匹配。使用算法1.2求取ALBP特征，并求取其相似度 ，将相似性集合作为新特征并形成一个归一化的新特征 。
4)按照行人面积占图像块面积的比例，以60 为分界，分布采用径向基核函数 和线性核函数 。K(xi,x)建立图像特征和图像人数的SVR(支持向量回归机)模型可使用opencv中的SVM或libsvm，输出模型估计参数 。
-Population density detection of video images, a variety of crowd density scenes crowd counting algorithm:
Algorithm functions: a mathematical relation between the image features and the number of images
Algorithm Input: training sample image 1,2 ... K
Algorithm output: model estimation parameters, reference image
Algorithmic process: 1) the training sample image into blocks (algorithm 1.1)
2) by 1.2 algorithm to calculate the corresponding training samples of each block ALBP features normalized, then K-means algorithm (algorithm can be used opencv library implementation, no longer describe the algorithm), the image block is divided into k (k <K) class, gets k (k <K) clustering centers, namely the reference image
3) conduct of image block matching with the reference image. 1.2 ALBP characterized using an algorithm to strike, and strike the similarity, the similarity of a set of new features and forming a normalized new features.
4) pedestrian area accounted for in Platform: |
Size: 4759552 |
Author:徐云华 |
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Description: Opencv FSBMA motion estimation 實作-Implement full-search block-matching algorithm (FSBMA) to estimation the motion vectors of each frame in a video sequence.
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Use the simulated shaken video to test the FSBMA motion estimation.
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Display the motion-compensated frames using the estimated motion vectors.
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Display the displaced frame difference (DFD) frame.
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Examine the estimated motion vectors to see if the simulated global frame motion in the input video can be found by the FSBMA? Platform: |
Size: 20443136 |
Author:lu you |
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Description: 数字视频技术的实验,关于穷尽块匹配算法的matlab程序及实验报告,,(Experiment of digital video technology, about the end of block matching algorithm matlab and experiment report,,) Platform: |
Size: 434176 |
Author:BWgtt%5F769
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Search - block-matching algorithm opencv