> I am a layman at this process, but have been following the group with
> interest for over a year. My first exposure with user based clients was
> with a company called Riya that was amazing and said they performed 3D
> facial recognition and more likely than not found the correct faces and
> eerily found many familial and age faces - even in background images. Like
> I said, I am not the hardcore scientist here, but interested in the
> applications of facial recognition and how it is, and will be applied. Now
> Picasa (Google.com) has facial recognition like Iphoto (although I believe
> it is better.
> My question - has anyone here worked with the Google Picasa solution and do
> you know what libraries/processes they are using.
> Thank you,
> Chris
> -----Original Message-----
> From: face-rec@googlegroups.com [mailto:face-rec@googlegroups.com] On Behalf
> Of Vaughan
> Sent: 2009-10-18 12:53 PM
> To: Face Recognition Research Community
> Subject: Optimizing image processing
> Hi everyone
> I am doing an undergraduate project for image recognition, and I've
> implemented my own training system using a variant of Adaboost,
> Cascades and Haar Features.
> My problem is that I'm experiencing a bottleneck when computing the
> weighted error of each weak classifer, since each classifier (of which
> there are 200,000+) must be evaluated on each image (of which there
> are at least 3000).
> I know this is more of a platform specific question, but I was hoping
> that someone possibly knows a technique which is used to do this (i.e.
> fast image iteration) and is generic enough to be applied to any
> platform (such as C#,C++ etc). For example, one may choose to tile all
> images together to create a single large image (though this would not
> be practicle for my case).
> Any insight would be appreciated.
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