I remember the eigenvector analysis of the original paper [1] wasn't terribly inaccessible. I think an alternative title for this blog post could be "Intuitively Understanding the Harris Corner Detector Optimizations".
PSA : The Harris Corner detector, while interesting to understand if you like linear algebra, is not exactly what you'd call state of the art in the feature detection layer of computer vision.
I believe the SIFT algorithm is most commonly used. Harris struggles when features change in scale between images, whereas SIFT does not. Harris can be outfitted with a Laplacian pyramid to overcome the scale issue though.
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[ 4.3 ms ] story [ 65.1 ms ] thread[1] https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&d...
In terms of tech that's advancing at the moment? ML techniques. https://co-tracker.github.io/ if you want to track individual points, https://github.com/matterport/Mask_RCNN and its descendents if you want to detect, say, the cover of a book.