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4 votes
Accepted

Useful natural "Hilbert-like" $n$-uples and $n$-fold "analytic signals

The generalisation of the concept of an analytic signal is not straight forward. I'm quite certain however that looking for such a generalisation with quarternions (or even octonions) will not turn ...
Jazzmaniac's user avatar
  • 4,583
3 votes
Accepted

What Is an Oriented Gaussian Second Derivative Filter

Unless mentioned otherwise withing the context the classic interpretation of Second Derivative Gaussian Filter is indeed (a) in your question: $$ L \left( x, y, \theta \right) = \cos \left( \theta \...
Royi's user avatar
  • 19.7k
2 votes

Determinant of Hessian approximation (SURF)

I think $w$ is a factor that makes the ratio of $D_{xy}$ to $D_{yy}$ the same as $L_{xy}$ to $L_{yy}$. This is so the value of the determinant for the simplified kernel roughly matches that of the ...
geometrikal's user avatar
  • 3,616
2 votes
Accepted

Feature matching of images without corners

I have referred to Stage I.D of this tutorial. Hope this helps. http://www.robots.ox.ac.uk/~vgg/practicals/instance-recognition/index.html#stage-id-improving-sift-matching-using-a-geometric-...
Arka Sadhu's user avatar
2 votes
Accepted

Are location in BRIEF feature descriptor reused?

When using a randomized pattern in BRIEF, this means that you computed random positions inside the patch once in an offline procedure, then used these random locations every time you computed the ...
sansuiso's user avatar
  • 3,937
1 vote

Is there a way to measure an image SNR blindly?

Without any knowledge of the clean image, with completely arbitrary image content? No. Because what if the image is a perfect portrait of noise? Without prior knowledge that an image is somehow &...
TimWescott's user avatar
  • 12.9k
1 vote

Invariances of FFT-based Image-Registration vs. SIFT-Features

I don't understand whether these processes are also invariant to object-alterations! They are not. How would the extracted fft-features look, if I alter the object (scratches, marks, dents etc.)? ...
A_A's user avatar
  • 10.7k
1 vote

Corner detector vs feature detector

A couple of confusions here. Features refer to some form of lower dimensional descriptors that explain a (potentially local) region of interest. They are useful in converting the appearance into ...
Tolga Birdal's user avatar
  • 5,465
1 vote

Useful natural "Hilbert-like" $n$-uples and $n$-fold "analytic signals

In this paper: "On the p-norm of the truncated Hilbert transform" by McLean and Elliot they say that the Hilbert transform is the only bounded integral operator on $L^p(\mathbb{R})$ that commutes with ...
geometrikal's user avatar
  • 3,616
1 vote

Efficient Hessian-Laplace blob detector implementation

You certainly can approximate Gaussian Blur by Box Filter which can be calculated by Integral Image. From that you can do Difference of Gaussian which is an approximation of the Laplacian of Gaussian. ...
Royi's user avatar
  • 19.7k
1 vote

Feature extraction/reduction using DWT

A notion that fits wavelets well is that of NLA, non-linear approximation. Given a length $N$ signal $[x_n]$, and its transformation coefficients $[X_m]$ (of length $M$) under transform $\mathbb{T}$. ...
Laurent Duval's user avatar
1 vote

How Hessian feature detector works?

For another perspective on using $\mathcal{H}$, remember that the first derivatives ($I_{x}, I_{y}$) are the slope at a point, and tell how strongly an image is changing in the $x$ or $y$ direction. ...
Scott Staniewicz's user avatar
1 vote

Scale and Rotation invariant feature descriptors

If you remap a local patch around a feature point to log–polar coordinates (with the origin in the point of interest), scale changes correspond to a translation along the log–radial axis, while ...
HelloGoodbye's user avatar
1 vote
Accepted

Sum of Squared Intensity Difference for block matching with ORB features, c++

Your results look reasonable. However, you're likely to get a somewhat unreliable result: the good matches are located in a small portion of the image, while a large spread would help in getting ...
sansuiso's user avatar
  • 3,937
1 vote

Understanding of Histogram-of-Oriented-Gradients

How this 36*1 came and how we calculated it? HOG is an algorithm which: works on a portion of the image, called "detection window"; divides the "detection window" in a certain number of cells; ...
rainbow's user avatar
  • 197
1 vote

Finding Local mean value of pixels of window

This is basically a filter which calculates the mean. In MATLAB you can achieve this using: mK = ones(w, w) / (w * w); mGBar = imfilter(mG, mK); Basically the ...
Royi's user avatar
  • 19.7k
1 vote
Accepted

How can I extract information about timbre from a .wav file. In which form can I study those features?

I think the time history of the wave file is enough to obtain all sorts of features. There are mathematical formulae to extract the features from a given time series. Some important features are: ...
Debasish Jana's user avatar
1 vote

Principal Component Analysis (PCA) on Convolutional Neural Network (CNN) Features

We are applying something similar like so: A CNN is trained on a particular image dataset. PCA (or some other transform) is performed on the feature vectors to obtain the main axes of variation. The ...
geometrikal's user avatar
  • 3,616
1 vote

Principal Component Analysis (PCA) on Convolutional Neural Network (CNN) Features

I'm not into details of this specific case but I can see some logic. A convolution layer can be reformulated as a Matrix Multiplication: $$ y = W x $$ Let's say we trained on Data Set $ {x}^{1} $ ...
Royi's user avatar
  • 19.7k
1 vote

Principal Component Analysis (PCA) on Convolutional Neural Network (CNN) Features

It does appear that the (re)ranking code is using the wrong dataset, i.e. the Oxford model with the Paris images. This question was raised in the following github issue: wrong dataset name #6. ...
ruoho ruotsi's user avatar
  • 1,770
1 vote
Accepted

How to recognise different symbols from their slope ? like (<,>,^) etc

My way of doing it would be: Extract LBP feature vectors for the reference symbols are store it. Now extract LBP feature vector of the test symbol. Compare it with the list of available reference ...
Navin Prashath's user avatar
1 vote

Can I use standard computer vision techniques for images taken in the NIR spectral range?

if it is possible to employ standard stereo matching algorithms like block-matching to images taken in the NIR spectrum and if so would it be possible (of course depending on the conditions) to obtain ...
A_A's user avatar
  • 10.7k
1 vote

Can I use standard computer vision techniques for images taken in the NIR spectral range?

I have a collection of 170 reflectance spectra of various "materials" (such as ripe brown banana and asphalt) attributed to Ron Gershon of Eastman Kodak. I believe they are diffuse reflectance, which ...
Olli Niemitalo's user avatar
1 vote

Can I use standard computer vision techniques for images taken in the NIR spectral range?

As far as I know, it is a common practice to use regular image processing techniques in this field. In fact I have recently finished a project in this field. if it is possible to employ standard ...
MimSaad's user avatar
  • 1,976

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