Yes you are right.  In video there are continuous streams of data for
objects as well as multi-perspectives and dynamics of the objects, IOW more
information.  So mining info out of video should produce in general higher
quality results than static images.  Then there are various tricks to use to
lower analysis resources like looking for changes over time by small sample
probing, skipping frames at exponential backoff rates., etc..  And the more
information you have as to what the video is before analysis the better. 

 

Why do you say that should we train ourselves to prefer solutions that use
more computing power?  Is this because those solutions in general are more
whole and manageable verses tweaked, hacked and optimized with loss of
adaptability?

 

John

 

 

From: Russell Wallace [mailto:[EMAIL PROTECTED] 

I haven't done any video analysis myself, but it should be easier than other
data types such as static images. Think of it this way: each frame of video
is an image - except that other frames give you extra constraints. The added
information is an asset, it makes things easier. Sure it uses more computing
power, but that's not the limiting resource, and we need to train ourselves
to actively prefer solutions that use more computing power. 

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