vlfeat | 易学教程

计算机视觉、机器学习相关领域论文和源代码小集合

阅读更多关于计算机视觉、机器学习相关领域论文和源代码小集合

一、特征提取Feature Extraction： · SIFT [1] [ Demo program ][ SIFT Library ] [ VLFeat ] · PCA-SIFT [2] [ Project ] · Affine-SIFT [3] [ Project ] · SURF [4] [ OpenSURF ] [ Matlab Wrapper ] · Affine Covariant Features [5] [ Oxford project ] · MSER [6] [ Oxford project ] [ VLFeat ] · Geometric Blur [7] [ Code ] · Local Self-Similarity Descriptor [8] [ Oxford implementation ] · Global and Efficient Self-Similarity [9] [ Code ] · Histogram of Oriented Graidents [10] [ INRIA Object Localization Toolkit ] [ OLT toolkit for Windows ] · GIST [11] [ Project ] · Shape Context [12] [ Project ] · Color Descriptor

VLFeat installation for Python

阅读更多关于 VLFeat installation for Python

问题 I am new to Python and I want to install VLFeat on Ubuntu (13.04). I am using Eclipse 3.8. For Python, I have installed the PyDev extension on Eclipse. I have installed Numpy, but I don't know how to install VLFeat. I tried to use their website, but I can't get anything for Python. I have downloaded packages, but I don't know how to install them. 回答1: The Menpo Project provides a wrapper around VLFeat: it's called cyvlfeat. To install cyvlfeat, we strongly suggest you use conda : conda

matlab练习程序（点云表面法向量）

阅读更多关于 matlab练习程序（点云表面法向量）

思路还是很容易想到的： 1.首先使用KD树寻找当前点邻域的N个点，这里取了10个，直接调用了vlfeat。 2.用最小二乘估计当前邻域点组成的平面，得到法向量。 3.根据当前邻域点平均值确定邻域质心，通常质心会在弯曲表面的内部，反方向即为法线方向。 vlfeat在这里下载，配置参考这里，rabbit.pcd 下载地址处理效果如下：原始点云：点云表面法向量，做了降采样处理：兔子果断变刺猬。 matlab代码如下： clear all; close all; clc; warning off; pc = pcread( ' rabbit.pcd ' ); pc =pcdownsample(pc, ' random ' , 0.3 ); % 0.3 倍降采样 pcshow(pc); pc_point = pc.Location ' ; %得到点云数据 kdtree = vl_kdtreebuild(pc_point); %使用vlfeat建立kdtree normE = []; for i= 1 :length(pc_point) p_cur = pc_point(:,i); [index, distance] = vl_kdtreequery(kdtree, pc_point, p_cur, ' NumNeighbors ' , 10 ); %寻找当前点最近的10个点 p

Getting stuck on Matlab's subplot mechanism for matching images' points for vlfeat

阅读更多关于 Getting stuck on Matlab's subplot mechanism for matching images' points for vlfeat

问题 I am doing vlfeat in Matlab and I am following this question here. These below are my simple testing images: Left Image: Right Image: I did a simple test with 2 simple images here (the right image is just rotated version of the left), and I got the result accordingly: It works, but I have one more requirement, which is to match the SIFT points of the two images and show them, like this: I do understand that vl_ubcmatch returns 2 arrays of matched indices, and it is not a problem to map them

VLFeat - How to fix “Warning: Name is nonexistent or not a directory”?

阅读更多关于 VLFeat - How to fix “Warning: Name is nonexistent or not a directory”?

问题 I downloaded the VLFeat lib from its git repository! I followed the instruction in the installation page. But when I ran the vl_setup command I got this warning: Warning: Name is nonexistent or not a directory: ..\Adv. 3D Computer Vision\vlfeat\toolbox\mex\mexw32 So follow some steps mentioned in MathWorks website, like 1,2,3 but the problem didn't solve. I trace the vl_setup.m file and according to the error statement it can not find the mexw32 folder. but there wasn't any folder like that

cv::Mat memory is not released even after calling release()?

阅读更多关于 cv::Mat memory is not released even after calling release()?

问题 I've written a method where an image descriptor (like OpenCV SIFT or VLFeat Dense SIFT) computes the descriptors for a set of images (save in std::vector<std::string> files ). The descriptor is called through ComputeDescriptors(image, descriptorMatrix) where it fills descriptorMatrix with the descriptors computed from. Then I randomly pick samples (usually 50) descriptors and push the sampledDescriptors matrix in the returned std::vector<cv::Mat1f> descriptors . This is the code: void

Running VLFeat setup using OCTAVE (OS: Windows 7)

阅读更多关于 Running VLFeat setup using OCTAVE (OS: Windows 7)

问题 Is there a clear documentation about running VLFeat setup using Octave (3.8.2) on windows (7) machines ? 来源： https://stackoverflow.com/questions/25391974/running-vlfeat-setup-using-octave-os-windows-7

SLIC c++ segmentation

阅读更多关于 SLIC c++ segmentation

问题 Im trying to segment an image using SLIC in OpenCV. Im trying to use the following function: void vl_slic_segment ( vl_uint32 * segmentation, float const * image, vl_size width, vl_size height, vl_size numChannels, vl_size regionSize, float regularization, vl_size minRegionSize ) the #include is fine and the linking to libraries is fine. I just need to know how can I pass the image to this function. the image parameter in this function is of type float const * and I dont know how to convert

OpenCV-Python Dense SIFT Settings

阅读更多关于 OpenCV-Python Dense SIFT Settings

问题 This is a follow-up question to the previously posted question about using OpenCVs dense sift implementation in python (OpenCV-Python dense SIFT). Using the suggested code for a dense sift dense=cv2.FeatureDetector_create("Dense") kp=dense.detect(imgGray) kp,des=sift.compute(imgGray,kp) I have the following questions: Can I access any of the DenseFeatureDetector properties in python? Set or at least read? What is the logic behind c++s FeatureDetector::create becoming pythons FeatureDetector

What's the order of parameters in vl_ubcmatch?

阅读更多关于 What's the order of parameters in vl_ubcmatch?

问题 I am using VLFEAT implementation of SIFT to compute SIFT descriptors on two set of images: queries and database images. Given a set of queries, I'd like to obtain the closest descriptors from a big database of descriptors, for which I use vl_ubcmatch. Having vl_ubcmatch syntax as MATCHES = vl_ubcmatch(DESCR1, DESCR2) I obtain different results if I input the query descriptors first and the database descriptors as a second parameter or the other way around. Which is the correct syntax? 1)