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Short answer is: you can’t apply Trilinear Inerpolation.
Let’s start with 2x2x2 blocks. Each block, is represented by it’s centre pixel ( 1,2,3,4 in ugly yellow on my sketch). Each pixel is located at the corner of a cell.
A pixel (the red dot), will be shared by up to 4 blocks that overlap.
With 3x3x2 block each block centre pixel will be also a cell centre pixel. And each cell pixel will be shared with up to 9 blocks.
You can’t use Trilinear interpolation. multilinear interpolations require 2^D samples. So you’ll need to choose a different way to assign the weights.
Remember that we’re not interested in interpolating values, but using the interpolation coefficients as weights.
Some options that you may use (haven’t tested them).
Inverse distance weighting: (trivial and easy, but I remember Euclidean norms didn’t work work well with images, still give it a chance)
Go 4x4x2 and use bicubic interpolation + linear for the 3rd dimension.
Check if it’s possible to obtain weight out of Lagrange or cubic spline polynomials.
Use QR decomposition to find a linear solution for the overfitted problem.
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solved Pyramidal Histogram Of Oriented Gradients – Trilinear interpolation

