Applying old things to new platforms has become common in recent times, here’s my contribution. I recently developed a video summary tool based on FFMPEG and Lire for a friend … just to test if common approaches are usable in a specific domain. Video summarization – especially of small videos – is a rather easy thing. You just need to find a number of frames with maximized pairwise difference, to cover a maximized visual range of the video. I applied my tool on YouTube and got the following summaires for the “hippo bathing” video:
Based on the CEDD descriptor the most important keyframe is really chosen well – just watch the video to know what I mean
With the auto color correlogram feature the dog is not explicitely part of the picture. However the first frame chosen (the big one) gives a good impression on the “bathing” part.
With the Gabor texture feature the dog gets prominent in the first place. Noite that the result is quite the same as the result kwith the Tamura texture feature not shown here.
With the most simple feature (RGB color histogram with L2 distance) the summary also looks appealing. There is a frame featuring the dog, one showing the whole scene and one for the hippo.
All in all I think the results are quite appealing. The runtime of my implementation is a fraction of actual video play time. Perhaps I’ll find some time to present the whole thing tomorrow at the barcamp 😉