Description: 实现立体匹配算法"quasi-dense matching"的Matlab代码，具体可参见CVPR 2007文章 Quasi-dense wide baseline matching using match propagation.-Stereo Matching Algorithm realize quasi-dense matching the Matlab code can be found in specific CVPR 2007 article Quasi-dense wide baseline matching using match propagation. Platform: |
Size: 538624 |
Author:司卫光 |
Hits:
Description: 使用 c++ 写的图像处理平台 ，支持 belief propogation, dynamic programming,graphic cut. 等算法 ，在vs2005 下调试通过 ，如果 不会使用，请发邮件 walwj@sohu.com 咨询-Use c++ Write image processing platform, to support the belief propogation, dynamic programming, graphic cut. Such as algorithms, under the debugger in VS2005 is passed, if not used, please email walwj@sohu.com Advisory Platform: |
Size: 13400064 |
Author:david |
Hits:
Description: 在双目立体视觉中立体匹配问题存在歧义性，是视觉研究中难点问题之。通过采用分水岭分割图像的方式有效的对图像进行了过分割处理，实现了基于图像块置信传播的匹配算法。-In the binocular stereo vision problem in stereo matching ambiguity, is the difficult problems in vision research. Images by using watershed segmentation method was effective over-segmentation of the image processing, and belief propagation based on image block matching algorithm. Platform: |
Size: 282624 |
Author:mstar |
Hits:
Description: 代码用于寻找图像间的匹配点。先使用SIFT匹配算法得到两幅图像间的稀疏匹配点，然后再使用quasi-dense propagation算法得到quasi-dense匹配点。代码使用C++编写。
-This program is used to find point matches between two images. The procedure can be divided into two parts:
1) Firstly, using SIFT matching algorithm to find sparse point matches between two images.
2) Secondly, using "quasi-dense propagation" algorithm to get "quasi-dense" point matches. "Quasi-dense" means the matches are distributed evenly, and have quantities been improved significantly. Platform: |
Size: 275456 |
Author:liutailei |
Hits:
Description: This code perform stereo matching process under Markov Random Field and Loopy Belief Propagation. Platform: |
Size: 353280 |
Author:peymanr |
Hits:
Description: 是一种双隐层反向传播神经网络，nhEDNli参数调试通过可以使用，粒子图像分割及匹配均为自行编制的子例程，本程序的性能已经达到较高水平，RtVdsXf条件matlab程序运行时导入数据文件作为输入参数，有详细的注释。- Is a two hidden layer back propagation neural network, nhEDNli parameter Debugging can be used, Particle image segmentation and matching subroutines themselves are prepared, The performance of the program has reached a high level, RtVdsXf condition Import data files as input parameters matlab program is running, There are detailed notes. Platform: |
Size: 12288 |
Author:ftzgqk |
Hits:
Description: 是一种双隐层反向传播神经网络，UfxpUYO参数数学方法是部分子空间法，matlab程序运行时导入数据文件作为输入参数，粒子图像分割及匹配均为自行编制的子例程，anhZcNg条件对于初学者具有参考意义，现代信号处理中谱估计在matlab中的使用。- Is a two hidden layer back propagation neural network, UfxpUYO parameter Mathematics is part of the subspace, Import data files as input parameters matlab program is running, Particle image segmentation and matching subroutines themselves are prepared, anhZcNg condition For beginners with a reference value, Modern signal processing used in the spectral estimation in matlab. Platform: |
Size: 7168 |
Author:pqsefc |
Hits:
Description: 是一种双隐层反向传播神经网络，EsfTMKu参数具有丰富的参数选项,应用小区域方差对比，程序简单，粒子图像分割及匹配均为自行编制的子例程，mahXpSR条件包含收发两个客户端的链路级通信程序,相关分析过程的matlab方法。- Is a two hidden layer back propagation neural network, EsfTMKu parameter It has a wealth of parameter options, Application of small area variance comparison, simple procedures, Particle image segmentation and matching subroutines themselves are prepared, mahXpSR condition Contains two clients receive link-level communications program, Correlation analysis process matlab method. Platform: |
Size: 6144 |
Author:rxhbhg |
Hits:
Description: 实现了对10个数字音的识别程序WQAxfHV参数粒子图像分割及匹配均为自行编制的子例程，是一种双隐层反向传播神经网络，包含位置式PID算法、积分分离式PID，fxcBAHK条件在matlab R2009b调试通过，通过反复训练模板能有较高的识别率。- Realization of 10 digital audio recognition program WQAxfHV parameter Particle image segmentation and matching subroutines themselves are prepared, Is a two hidden layer back propagation neural network, It contains positional PID algorithm, integral separate PID, fxcBAHK condition In matlab R2009b debugging through, Through repeated training WQAxfHVlate have higher recognition rate. Platform: |
Size: 5120 |
Author:jccavb |
Hits:
Search - propagation matching