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VLFeat wrapper
The keypoint detector and descriptor classes implemented are a wrapper of the amazing vlfeat functionalities. There are three separated classes, they are:
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Triangulation
Problem definition
Given camera matrices (\(P, P'\)), or fundamental matrix \(F\), and measured image points \(x\) and \(x'\), estimate the 3D point \(X\) that minimizes some cost function.
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Git cheatsheet
Exclude a directory
Create a
.gitignorefile in root, and add the directory name in itdir_name/ -
An introduction to the `mex` file and useful implementations
I use mostly Matlab to test my algorithms, it’s super easy to implement and fast enough for matrix computation. However, for some computationally heavy tasks that is hard to implement as matrix computation, I would normally turn to C++ for its efficiency. Thus I need an additional
mexfile so that my Matlab code can use the C++ code. To do so, most of the job required is to convert matlab data into C++ data, and I create some methods just for this purpose so that I don’t need to do this all over again next time. So here it is. -
C++ implementation of a image class
The internal data structure used to store image is a vector of
unsigned char. Here are a list of basic functionalities included in theImageclass -
Change to the al-folio theme
This Jekyll theme is developed by Maruan Al-Shedivat, which is modified from the original template -folio developed by Lia Bogoev. Thanks to those two for this clean, and simplistic design.
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C++ implementation of a numeric class
One of the most widely used matrix and linear algebra library is Eigen. This is a header only library, thus no compiling or installation needed. I decided to write a wrapper class based on this library, so here it is.
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Estimation of fundamental matrix
The epipolar geometry is the intrinsic projective geometry between two views, which is independent of scene structure, and only depends on the camera’s internal parameters and relative pose.
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Matlab implementation of bilateral filter
Bilateral filter
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Camera visualization in Matlab
I read somewhere that to be more efficient in a long run when it comes to implementing a library, the first thing you should implement is the code that does visualization. To 3D computer vision, the single most important or common place component is probably the camera. This is what we are going to do here.