11
votes
Accepted
Markov (Chain) image generators?
I've implemented this recently, basically it counts how many times each specific colour borders another colour to make up a frequency table. To generate an image, a random colour and position are ...
8
votes
Matrix free finite elements method for visualization in process tomography
To add to Dmitry's answer (copied over from the deleted version of this question):
Matrix-free finite elements are relatively well-known. For explicit methods for transient problems, this involves ...
7
votes
Accepted
Matrix free finite elements method for visualization in process tomography
Matrix-free method is a general name for a class of algorithms, rather than a particular method.
For example, consider solving the linear equation $Ax=b.$ If you were to solve this this problem using ...
5
votes
Accepted
Algorithms to extract trajectory lines out of 3D point clouds
I will summarize a couple of possibilities:
As a baseline, I would begin with a Hough transform kind of approach:
Iterative Hough Transform for Line Detection in 3D Point Clouds
Christoph Dalitz,...
5
votes
Accepted
Iterative camera calibration - No convergence
I have to tell you.
I implemented this algorithm (even double checked with other experienced people), however no luck. I guess, this worked for the authors, but with our data there was really no ...
3
votes
Accepted
Evaluate 3D Shape Descriptor
3D local feature descriptors for shapes are very well studied. Typically, people tend to represent the input as a set of points (point clouds) and try to characterize the local neighborhoods with ...
3
votes
Accepted
Compute point-spread-function between original and blurred image
We construct an operator based on the assumption that the system is a linear space invariant system. The blurred image is denoted $b$ and the input is denoted $x$.
Since the convolution is commutative,...
2
votes
Fitting orthogonal planes to a point set
Here I devise a novel strategy, based on only 3D points, that I think, would work.
I will parametrize a 3D plane by a point $\mathbf{p}$ and its normal $\mathbf{n}$.
Imaging you take a pair of ...
2
votes
Accepted
How to train a model to classify object trajectories?
Just some quick ideas from someone who works in the realm of feature extraction in physical systems modeling such as this: you want to find the simplest and strongest differentiating characteristics ...
2
votes
Is the inverse radon transform considered a linear operation?
For an operator $R$ to be linear, it has to satisfy two conditions:
$R(f+g) = Rf + Rg$ for any two operands $f,g$;
$R(\alpha f) = \alpha Rf$ for any operand $f$ and (real or complex) number $\alpha$.
...
2
votes
Algorithm to determine flat surfaces and camera orientation without specialized hardware
You are quite right, Augmented Reality benefits a lot from a combination of video/image analysis together with the data from motion sensors. Quote from Apple ARKit: Understanding World Tracking:
To ...
2
votes
Accepted
Polygon approximation with a circle
They just curve fit the two equations
$$
x(\omega) = h - b \sin(\omega) ~,~~
y(\omega) = k + a \cos(\omega)
$$
using a nonlinear curve fitting algorithm. However, the accuracy of the fit depends ...
2
votes
How to find fundamental matrix based on other fundamental matrix and camera movement?
I cannot help but suspect that the working function you've provided is less efficient than it can be, but I must also admit that I have only dabbled in computer vision myself. Here's a suggestion for ...
1
vote
Detect all geometric objects in an (edge) image
I propose a simple solution, but whether it works will depend on how well line following can separate the groups and how fast the ellips fitting works.
Step 1, follow lines to separate the edge points ...
1
vote
Detect all geometric objects in an (edge) image
A. Convex polygon inside convex shape
Since all objects are convex, if two endpoints of a line segment are inside an object the entire line is in the segment, and if all the edges of a convex polygon ...
1
vote
Methods to implement floor dirt detection algorithm
Here are some suggestions:
Whatever method you try, look at a large number of dirty floor samples to get an idea of the range of things - is it a darker area, is it streaks, etc.
For a simple idea, ...
1
vote
Algorithms to extract trajectory lines out of 3D point clouds
When the points belong to more than one curve, it will first be necessary to cluster them into curves. A possible approach is described together with a reference implementation in
Dalitz, Wilberg, ...
1
vote
Fitting orthogonal planes to a point set
I think your problem can be written as an optimization problem.
$\{x_i\}$ is the set of points for plane 1, $\{x_j\}$ for plane 2 respectively. Their orthonormal vectors are $n_1$ and $n_2$ with ...
1
vote
Integral image resizing
The formula says that the resized (smaller) image pixel at (x,y) is a bilinear approximation of the pixel at location (2ax+b, 2ay+b). Ignoring b for the moment, you can see that the scale factor (or &...
1
vote
Can software remove all distortion from image taken with 180-degree lens?
Software could never get rid of all the effects of distortion. The reason is that, if you do not operate in the hardware level, you could only make approximations about the real effects. Distortion ...
1
vote
Markov (Chain) image generators?
Blog post on an experimentation using Markov to recreate art:
https://magenta.as/using-machine-learning-to-make-art-84df7d3bb911
Code is on github made by @william-index:
https://github.com/william-...
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