Thread Subject: Face recognition technique for newbie

Hello there,

Hello I am starting a project on face recognition (yeah!!), but the problem is I am in very early stages also a newbie when it comes to matlab. I do not have a strong maths background know that matlab is the best language to use to implement a facial recognition system.

I was wondering if you could give me advice on what the best face recognition technique, but not too advance that it would take ages to program. This project is for a degree as you can understand there also exams I have to sit.

I have researched eigenfaces and hidden marklov model. I have heard that these methods are extremely mathematical and will take an immense time to program. Is there any techniques that are not mathematically intensive and carried out with a time period of say 2 months.

Any help will me hugely appreciated.

David

p.s. I keep my post short next time

 This might be too simple for what you are looking for but in case you are using color imagens try using HSV colorspace.
 This might sound strange, but all the races have the same skin color.
The only thing that varies is the saturation of the color. You can detect skin by looking at it?s H(hue) value, with a low margin, and ignoring S (saturation)...
 Will also detect other skin areas, but it?s good place to start.

On Nov 21, 9:16 pm, "Ironic Prata" <lixodoiro...@hotmail.com> wrote:
>  This might be too simple for what you are looking for but in case you are using color imagens try using HSV colorspace.
>  This might sound strange, but all the races have the same skin color.
> The only thing that varies is the saturation of the color. You can detect skin by looking at it?s H(hue) value, with a low margin, and ignoring S (saturation)...
>  Will also detect other skin areas, but it?s good place to start.

-----------------------------------
I agree that this is a good, easy way to start. Of course it won't
work in all cases but if all the faces in your database are pretty
similar, it might work well enough for you to get a decent grade in
your class.

The three dimensional color gamut of skin taken on a calibrated
instrument such as a colorimeter or spectrophotometer is very
interesting - it looks like a boomerang shape. It goes more or less
out in one hue. It comes back in towards the L (or H or I) axis both
at the bright end, and the dark end, and it bows out for middle
intensity individuals. It makes sense if you think about it. You can
have color if you're not too pale or too dark. If your skin is very
very white, you're of course going to have a color near the V axis.
Likewise if your skin is very very black, you're also going to be near
the V axis. Only those people in between can have different
saturations (also called chroma) - of course they also have different
intensity values also (L, H, or I depending on which color space
you're using). So you can convert to HSV, find H in a certain range
regardless of S or V. Of course this will find all "flesh" colored
objects in the field of view but I assume you'll be having something
simple to practice with such as full frontal face images with little
other clutter in the field of view. If your images are taken with
different color temperature illumination (e.g. daylight, sunlight,
fluorescent light, xenon flash, incandescent lighting, etc.) then now
your boomerang shape is going to wobble around, taking different
angles as it juts out of the V axis. So now you're going to have to
allow a larger angular range of H values to take (remember the value
of the H channel represents the ANGLE of the hue - very important!).

You can look up my demo where I find things in monochrome.
http://www.mathworks.com/matlabcentral/fileexchange/25157
Just apply this to the hue channel after you've converted your rgb
image and that should be a good start.

"David Miller" <clothink121@hotmail.co.uk> wrote in message <hea3pn$qe7$1@fred.mathworks.com>...
> Hello there,
>
> Hello I am starting a project on face recognition (yeah!!), but the problem is I am in very early stages also a newbie when it comes to matlab. I do not have a strong maths background know that matlab is the best language to use to implement a facial recognition system.
>
> I was wondering if you could give me advice on what the best face recognition technique, but not too advance that it would take ages to program. This project is for a degree as you can understand there also exams I have to sit.
>
> I have researched eigenfaces and hidden marklov model. I have heard that these methods are extremely mathematical and will take an immense time to program. Is there any techniques that are not mathematically intensive and carried out with a time period of say 2 months.
>
> Any help will me hugely appreciated.
>
> David
>
> p.s. I keep my post short next time

www.advancedmcode.org/face-recognition-based-on-fractional-gaussian-derivatives.html

www.advancedmcode.org/face-detection-system.html

www.advancedmcode.org/fast-and-accurate-face-identification-using-overlapping-dct.html

Hello there,
I am looking for a software the can recognise THE PRESENCE of a face, wether the picture is taken from the front or from the side.
More concrete: if you take a picture from the side of a car (let us say the side window), and there is a person sitting in the rear seat, does your software (or any other software?) allows to detect that there is a human being??

With kind regards,

Robert De Beukelaer

"David Miller" <clothink121@hotmail.co.uk> wrote in message <hea3pn$qe7$1@fred.mathworks.com>...
> Hello there,
>
> Hello I am starting a project on face recognition (yeah!!), but the problem is I am in very early stages also a newbie when it comes to matlab. I do not have a strong maths background know that matlab is the best language to use to implement a facial recognition system.
>
> I was wondering if you could give me advice on what the best face recognition technique, but not too advance that it would take ages to program. This project is for a degree as you can understand there also exams I have to sit.
>
> I have researched eigenfaces and hidden marklov model. I have heard that these methods are extremely mathematical and will take an immense time to program. Is there any techniques that are not mathematically intensive and carried out with a time period of say 2 months.
>
> Any help will me hugely appreciated.
>
> David
>
> p.s. I keep my post short next time

It is better to have a long post that explains your problem, than a short one which doesn't provide all the information required to provide an answer.

Regarding your Face Recognition problem, look here

http://www.mathworks.com/matlabcentral/fileexchange/?term=Face+Recognition

for some very well regarded solutions/partial solutions. Try them, understand them and base your program on your understanding of them - don't plaigarize them; your professor probably visits this site;-)

Regards

Dave Robinson