Toby Murray-2 wrote
> 
> Well if you really want harsh lighting, you might look at the video I
> just uploaded the other day from biking across Kansas.
> 
Wow, those really are difficult lighting conditions! Even as a human one has
trouble reading the speed limit signs in those videos.

Apart from the Sun, those videos seem like some ideal test cases for this
system. High quality, and the type of rural road where this system could be
most useful. Very few POIs and then the odd road sign every couple of
minutes. So automatically condensing those 18 minutes into a few relevant
frames that have interesting content could really be a time saver.


Toby Murray-2 wrote
> 
>  It is full
> motion video too, not timelapse.
> 
I think under these conditions, the benefit of full motion video vs
timelapse can be particularly striking. Most of the time the road signs are
not readable due to the sun and only at very specific angles can you discern
the writing on the signs. With time laps video, chances are that one would
miss the short time frame where one can comparatively easily read the signs.

The full motion pictures might also allow for some other tricks to be
played. With the help of optical flow one can probably determine the depth /
distance from the camera and thus the size of objects. As street signs have
a well defined size, one could potentially use that as extra heuristics to
better identify road signs under these difficult conditions. Once one has
locked onto a sign and can track it through the video one can either choose
the best frames, or use classifiers that average across the multiple frames
in which the sign is viewable, hopefully increasing the accuracy of the
system. Depending on how Nikhil gets along, these kind of fancy computer
vision tricks are probably beyond the scope of the project though. But it
would be cool if one could try some of this out...


Kai

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