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Edit: I didn't make this clear, for this is for the possible future development of an application.

I am looking into individual facial recognition for an application, but an essential part of this seems to be a fairly large training set of images for each individual to be recognized.

Is it important for the images to be taken at different times in different environments, or could several images captured over a few seconds with a handheld camera possibly provide the necessary variations for a good training set?

(This isn't for human facial recognition, by the way, so existing tools and databases won't really help too much. I'm aware that 2D image recognition can not necessarily be applied to all species; let's just assume that it does work in my use case.)

Nick O.
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  • Is the image recognition software you are using specific to facial recognition or is it just basic image recognition? Also, once trained, will the test subject be under controlled position and lighting or will these vary greatly? – bcampolo Jan 04 '16 at 17:40
  • I haven't settled on any specific software, but I expect to use local binary patterns, which can be used for image recognition in general. The lighting may vary considerably, but the position should be controlled. Edit: But, the end application should be specifically targeted at facial recognition. – Nick O. Jan 04 '16 at 17:58

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This paper may answer some of your questions: http://uran.donetsk.ua/~masters/2011/frt/dyrul/library/article8.pdf

From the pattern classification point of view, a usual problem in face recognition is having a plethora of classes and only a few, possibly only one, training sample(s) per class. For this reason, more sophisticated classifiers are not needed but a nearest-neighbour classifier is used.

While I'm not an expert on the subject, it appears to be a common problem to have only one image per person as a training sample and one that has been solved with at least some level of accuracy in controlled lighting/positional situations.

To specifically answer your question, a training set that had multiple images of each person with little or no variation ("several images captured over a few seconds with a handheld camera"), would not be as valuable as one that had more variation (e.g. different facial expressions, lighting, backgrounds).

bcampolo
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