Description: 基于视频运动对象的快速提取
采用了差分法,光流法以及贝叶斯估计-Moving Object Based Video Fast extracted using a finite difference method, optical flow estimation method and the Bayesian Platform: |
Size: 70730 |
Author:njustyw |
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Description: 基于视频运动对象的快速提取
采用了差分法,光流法以及贝叶斯估计-Moving Object Based Video Fast extracted using a finite difference method, optical flow estimation method and the Bayesian Platform: |
Size: 70656 |
Author:njustyw |
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Description: This method is used for tracking wavelet/optical flow-based
detection for automatic target recognition in the following paper:
Dessauer, M. and Dua S. “Wavelet-based optical flow object detection, motion estimation, and tracking on moving vehicles” Platform: |
Size: 1355776 |
Author:MemoSergey |
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Description: 一个运动目标检测程序，可以很好的为光流法作铺垫-A moving object detection procedures can be very good to pave the way for the optical flow Platform: |
Size: 61440 |
Author:mapeng |
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Description: 一种利用光流法检测运动物体的程序，供初学者参考。-Optical flow method by means of a moving object detection procedures for advanced users. Platform: |
Size: 19495936 |
Author:秦垚 |
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Description: 完成光流法算法。用于图像边缘的提提取，运动目标的检测。可直接使用。
-Completion of the algorithm of optical flow method. Mention for image edge extraction, moving object detection. Can be used directly. Platform: |
Size: 2048 |
Author:勇敢 |
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Description: 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, background subtraction method, optical flow detection and tracking method Kalman filtering, feature-based optical flow method, and various methods of comparison, pointing out its strengths and weaknesses and the scope of application, and the experimental results of differential and background difference time-domain method Platform: |
Size: 249856 |
Author:hengluo |
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Description: 基于光流算法的图像分割，能对两帧图像检测出其中运动的物体，并对其进行分割-Image segmentation based on optical flow algorithm, two frames to detect moving object, and carries on the segmentation Platform: |
Size: 1046528 |
Author:杨小平 |
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Description: 光流法区分摄像头抖动和运动对象，仅供参考，实时性不好保证-Optical flow method to distinguish between camera shake and a moving object, for reference, real bad guarantee Platform: |
Size: 1024 |
Author:徐扬 |
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Description: 运用光流法的来对运动物体进行跟踪，输出特征点的位置和变化情况。-Using the optical flow method for moving object tracking, and output the position of the feature points and changes. Platform: |
Size: 2048 |
Author:miss |
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Description: 常见的目标检测方法主要有光流法，帧差法和背景模型法。光流法利用背景和运动目标的运动速度不同进行目标检测，计算量较大；帧差法对连续几帧图像的背景进行配准，通过前后帧的差分图像分离出运动物体；背景差法根据已知背景对图像进行差分，在运动背景下需要对背景模型进行更新。-Common target detection methods are mainly optical flow method, frame differential method and background model method. Optical flow method with different background and moving target movement speed target detection, large amount of calculation In successive frames image frame differential method for registration, the background of moving object was isolated through front and rear frame difference image Background difference method based on the background of image difference known, under the background of sports need to update the background model.
Platform: |
Size: 466944 |
Author:shitao |
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Description: 光流传感器源码，做机器人视觉的可以参考，根据摄像头的数据判断物体两个轴的移动速度-Source optical flow sensors, robot vision can make a reference, according to the data of the camera moving speed of the object is determined two axes Platform: |
Size: 1247232 |
Author:许可 |
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Description: ：提出一种基于SURF 与光流法相结合的增强现实局部跟踪注册方法。采用光流法对移动对象区域进行跟
踪，利用SURF 算法仿射、尺度不变性及运算速度快的优点对该区域进行特征提取与匹配，利用相邻帧之间特征点的
匹配关系求得三维注册矩阵，在保持注册精确性的同时降低了系统运算时间。实验结果表明该方法达到了实时跟
踪与准确注册的效果，并且在环境变化时保持了较好的鲁棒性。-A tracking and registration method based on SURF and optical flow in the AR is proposed. The moving object
region is tracked by the optical flow method. This paper extracts and matches the features of the region with SURF because
the algorithm maintains advantages of affine invariance, scale invariance and fast computing speed. The final registration
matrix is calculated using the homographies between adjacent frames. This method reduces the computational time deeply
while the accuracy of the registration unchanges. Convinced by experimental results, this approach can work at almost real
time and achieves accurate registration, and can keep a good robustness in some environment changes. Platform: |
Size: 723968 |
Author:Liu Yaoyang |
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Description: Matlab based on the optical flow method of moving object detection, source code, available Platform: |
Size: 4096 |
Author:whpmatlab |
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Search - optical flow moving object