Map time/scene differences between two similar videos
This was an interesting read and it looks like you're not too far off! I think that what you have left to do is divide one of the signals into intervals (let's call it signal 1) and cross-correlate each segment of signal 1 with the entirety of signal 2. The peak in the cross-correlation will indicate where there is the strongest match for that segment in signal 2. You then calculate the difference in frames between where the segment was in signal 1 and where its strongest match is in signal 2.
The third step in the post you mentioned appears to be Kernel Density Estimation. The author placed a Gaussian at the center of each segment from signal 1. The standard deviation of the Gaussian, I assume is one-sixth the segment length, and the amplitude of the Gaussian is the frame difference. The Gaussian should extend from time 0 to the length of signal 2. He then summed all the Gaussians to obtained a continuous function.
I think you can achieve the same thing if you do the following: once you have the frame difference as a function of time, you convolve that function with a Gaussian whose standard deviation is one-sixth the segment length you used to divide signal 1.
I hope this helped!