New answers tagged computer-vision
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If you have access to the raw pixel data, you can implement binning in software too. They should be identical upto the step-size of the ADC, by which the quantized analog sum of pixels may differ from sum of quantized pixels.
Hardware binning has the advantage that it has to transfer less number of pixels, hence can operate at high fps compared to raw data ...
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After having researched and learned a little bit more about the pinhole camera model, I think I know the difference between the camera (or image) plane and the virtual plane (or image).
The virtual plane (or virtual image) doesn't physically exist, but it's only used to simplify the mathematical modeling and reasoning. How does it do that? The main ...
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They can. As Francesco mentioned, these problems can be solved with less correspondences. What makes the difference is how we formulate the problem. If we like a fast linear solution, then 8-points are required. For formulations using less number of points, the constraints are non-linear and typically involve either determinants or systems of polynomial ...
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If the camera has a shallow depth of focus and the background is mostly blurry and the foreground is only moving at one focal plane, why not use a simpler method, such as Template Matching?
Since the printing head is changing its angle of view with respect to the lens as it moves in the $x,y$ dimensions, you might have to use more than one templates but ...
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When you have the described convolution measurement, you can indeed recover your $X$ using sparse recovery methods. Some examples are, as you suggest, OMP, MP, or for example subspace pursuit (SP), compressive sampling matching pursuit (CoSaMP), iterative hard thresholding (IHT), a plethora of other variants of greedy recovery methods, as well as basis ...
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