From the post:
The OpenCV library provides us a greatly interesting demonstration for a face detection. Furthermore, it provides us programs (or functions) that they used to train classifiers for their face detection system, called HaarTraining, so that we can create our own object classifiers using these functions. It is interesting.
I am not sure about the “rapid” part in the title because the author points out he typically waits a week to check for results. 😉
I suppose it is all relative.
Assuming larger hardware resources, it occurred to me that face detection could be interest to topic map authors or more importantly, to people who buy topic maps or topic map services.
At some point, video surveillance will have to improve beyond the convenience store video showing a robbery in progress, to something more sophisticated.
It is all well and good to take video of everyone in the central parts of London, but other than spotting people about to commit a crime or recognizing someone who is a known person of interest, how useful is that?
Imagine a system that assist human reviewers with suggested matches not only to identity records but suggests links to other individuals either seen in their presence or who intersect at other patterns, such as incoming passenger lists.
Hopefully this tutorial will spark you thinking on how to use topic maps with video recognition systems.