I've been implementing my own HoG transform looking at different sources.
While the implementation in scikit-image seems to lack certain features
(multiple normalization schemes, general block overlap, Gaussian block
window, trillinear interpolation/weighting of bin assignments,...) these
don't seem to be that important, at least when applied to my current
problem (eye blink analysis).
Most of these would increase complexity, giving the implementation a
complicated look, with little gain. I've also been looking into some
practical improvements - integral histogram, separating the cell-block
histogram feature to use it with other dense feature transforms such as
LBP, a HoG visualization function that would render the visualization at
higher resolutions that the original image.
Would any of these be welcomed additions to scikit-image?