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I assume you mean Binnning at the Pixel Level before Demosaicing (Bayer Pattern) and resizing image after Demosaicing. The main difference has to do with the properties of the Noise. Demosaicing creates spatially correlated noise which means "Averaging" becomes less effective in reducing it. At RAW level noise is much whiter hence averaging is more ...


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Pretty much the same. The intrinsic calibration tells you the relationship between stuff "out there" relative to the camera's frame of reference and the image the camera makes. The extrinsic calibration tells you how to get from the camera's frame of reference to whatever your "global" frame of reference may be.


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Since no one answered this, I will post my attempt after further research. Here is my understanding after having thought about it more. Lets say we are using VGG-16 as the backbone. Step 1) Train a region proposal network with VGG-16 trained on imagenet (minus one layer popped off, and not including the network head). The important weights learned are those ...


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My attempt: You can treat an image as a discretization of the perspective projection of a continous 3D region, given a near and far plane. Using this discretization, filters used in signal processing can be used to modify the signal (a 2D array) for various purposes. These purposes include things like edge detection, image denoising, object detection, ...


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The plane at infinity has to be calculated as following: function plane = computePlaneAtInfinity(P, K) %Input % P - Projection matrices % K - Approximate Values of Intrinsics % %Output % plane - coordinate of plane at infinity % Compute the DIAC W^-1 W_invert = K * K'; % Construct Symbolic Variables to Solve for Plane at Infinity % X,Y,Z is the ...


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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 descriptors. This makes sense, as it means that when comparing descriptors you will actually compare the same locations, it's simply that the sampling pattern was ...


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