Skip to main content
Share Your Experience: Take the 2024 Developer Survey
15 votes

How to generate stereo image pair from a stationary mono camera?

You can't. You have video of the scene from a single vantage point. Without depth information, you can't infer what the scene would look like from another vantage point.
D.W.'s user avatar
  • 161k
14 votes

What is the difference between luma and luminance?

There are actually three related terms: Luminance is a physical measure which represents the luminous intensity per unit area of light travelling in some direction. The units are candela per square ...
Pseudonym's user avatar
  • 22.2k
13 votes

2D convolution: Flipping the kernel?

If you do not flip the kernel, you simply obtain a different operation that is called cross correlation. When the filter is symmetric, like a Gaussian, or a Laplacian, convolution and correlation ...
Andrea Asperti's user avatar
9 votes

How to generate stereo image pair from a stationary mono camera?

The terms you probably want to google for are "inferring depth maps". Just like your brain tricks you into seeing 3d if you close one of your eyes, you can heuristically recover depth maps from single ...
adrianN's user avatar
  • 5,951
7 votes

What is the difference between the fundamental matrix and the essential matrix?

I want to add one thing to @Dima's answer, just so things are absolutely clear: $E = (K')^TFK$ (note the transpose) You can see how this also captures that the fundamental matrix takes image ...
f.k's user avatar
  • 71
7 votes

Google DeepDream Elaborated

The idea of DeepDream is this: pick some layer from the network (usually a convolutional layer), pass the starting image through the network to extract features at the chosen layer, set the gradient ...
Maxim's user avatar
  • 640
7 votes

How does a predictive coding aid in lossless compression?

Huffman coding, as usually applied, only considers the distribution of singletons. If $X$ is the distribution of a random singleton, then Huffman coding uses between $H(X)$ and $H(X)+1$ bits per ...
Yuval Filmus's user avatar
5 votes
Accepted

High Dimensional Spaces for Images

From one perspective, a picture is a 2D image, because it has height and width. But from a machine learning perspective, we can think of a picture as a point in a high-dimensional space. In ...
D.W.'s user avatar
  • 161k
5 votes
Accepted

Hausdorff distance between two binary images according to distance maps

So I finally managed to do it, here's the answer for future reference. The idea is not to compute the distance map of the image, but of its complement. Here's a example to better understand : You ...
qcoumes's user avatar
  • 201
4 votes

Slicing clusters of non-black pixels from an image into separate images

It seems that you're just trying to find the connected components of a graph. In this case, the vertices are the non-black pixels and there's an edge between two pixels if they're at distance at most&...
David Richerby's user avatar
4 votes
Accepted

Computer vision: object detection with labels that are single coordinates

The state of the art in such problems is done these days via deep neural networks. Among others, two popular and recent approaches for solving the problem of detection and localization of objects are ...
Nathaniel Bubis's user avatar
4 votes
Accepted

Rearrange pixels to maximize visually distinguishable pattern

This will not be an algorithm in the usual sense. It's a bunch of heuristics that you may find useful. The main difficulty comes from the undefined nature of the phrase "visually similar". If I ...
aelguindy's user avatar
  • 1,807
4 votes
Accepted

Summed-area table for circular range queries

The best way is to approximate circle with hexagon or octagon as desciribed in expired patent US 6507676 B1. Further improvement is to add rectangles to octagon to get more circular shape or like ...
Evil's user avatar
  • 9,465
3 votes
Accepted

Does JPEG compression use a heuristic model similar to MP3?

There are several lossy aspects of the JPEG algorithm. The main one is quantization of high-order Fourier coefficients, and a more minor one is downsampling the color components. JPEG compression of ...
Yuval Filmus's user avatar
3 votes

Reconstructing a screen of permuted pixels

One approach is to exploit fact that if two pixels are adjacent, then their intensities will be highly correlated: the intensity of the first pixel (as a time series) will be highly correlated to the ...
D.W.'s user avatar
  • 161k
3 votes
Accepted

Which algorithm for counting the occurrences of a certain pattern (spots) in an image?

The best way to get an orientation is to read a textbook on computer vision or image processing. There are lots of techniques known, and that's often the best way to get an introduction to a broad ...
D.W.'s user avatar
  • 161k
3 votes

Extracting features for texture classification

If it is important for you to get a high accuracy, then use a convolutional neural network (ConvNet). These ConvNets hold the state of the art for most visual recognition tasks. If your training set ...
pir's user avatar
  • 131
3 votes
Accepted

What is the appropriate means of bias field in image processing?

Bias field is magnetic based inhomogenity in results of MRI, which comes from magnetic settings, patient position etc. This term has no standard definition in terms of image processing. Essentialy ...
Evil's user avatar
  • 9,465
3 votes
Accepted

How are the number of bytes less than the number of pixels in an image?

A colour image is typically digitalized using 256 levels for each of the 3 RGB channels. That gives 3 bytes per pixel. The trick to attain smaller file size is to apply some compression, to take ...
leonbloy's user avatar
  • 256
3 votes

Slicing clusters of non-black pixels from an image into separate images

You are probably looking for something like image segmentation.
adrianN's user avatar
  • 5,951
3 votes
Accepted

Applicability of Machine Learning on Images.

It looks plausible that this is the kind of problem machine learning will be good at. I suspect you might be able to achieve much higher accuracy, but the only way to know for sure is to try it. For ...
D.W.'s user avatar
  • 161k
3 votes

Algorithms to correct misspelled word?

Standard OCR software already incorporates this idea: it has a corpus of words, along with their frequency of occurrence, and uses this to correct errors. How does it work? OCR doesn't just output ...
D.W.'s user avatar
  • 161k
3 votes

Convolutional Neural Network with constant kernels

A fully connected layer is able to classify images better than random. If you make the kernels constant and there is still information in the result, the network is essentially only a FCN operating on ...
Martin Thoma's user avatar
  • 2,360
3 votes
Accepted

Given a low resolution video, is it possible to create a higher resolution image

It heavily depends on the setting, accuracy and goal, but shortly, yes, even considering practical application. Theoretically of course it is possible, with various (or used together) techniques like ...
Evil's user avatar
  • 9,465
3 votes

Sample K representative frames within a video

The question misses a lot of detail, so I will try to make an educated guess. I don't know of any specific algorithm for the task you are trying to achieve, but the first step towards your solution ...
João Gueifão's user avatar
3 votes
Accepted

How to prove that the erosion of a convex set by a convex set will result in a convex set?

(Convexity is closed under intersection) Given a family of convex set $C_i$, where $i\in I$ for some index set $I$, then $\cap_{i\in I}C_i$ is convex. In other words, the intersection of convex sets ...
John L.'s user avatar
  • 39k
3 votes
Accepted

what is meant by support of a filter?

Many filters, particularly linear time-invariant ones, are represented by a kernel function. The output of a filter at a point is calculated by a weighted average of all the points of the input where ...
Derek Elkins left SE's user avatar
3 votes

What is an algorithm to find the largest rectangle of white space in an image?

Subtract $254.9999999$ from all pixel values, so black corresponds to $-254.9999999$ and white to $0.0000001$. Find the 2D subrectangle with maximum sum. There are standard $O(n^3)$-time algorithms ...
D.W.'s user avatar
  • 161k

Only top scored, non community-wiki answers of a minimum length are eligible