Once the extracted data is available, then the cost of performing a comparison must be considered. One key cost to consider is that of extracting the data needed from each video for whatever comparison metrics are to be used. ![]() So we really care about the local cost of each comparison in several different domains: 1) Data storage, 2) compute resources, and 3) time. ![]() And the size of the database likely makes the use of cloud computing resources unfeasible. It is important that the comparisons be performed using the compute and time resources available: I doubt a solution that takes months to run will be very useful in a dynamic video database. This is a huge problem, so I've chosen to write a rather lengthy reply to try to decompose the problem into parts that may be easier to solve. Or am I going the completely wrong way? I think I can't be the first one having this problem but I have not had any luck finding solutions. ![]()
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