[Digikam-devel] GPU Implementation of image processing algorithms

[kunal ghosh]

Hi Aditya,

On Sun, Apr 18, 2010 at 10:26 AM, Aditya Bhatt <adityabhatt1991 at gmail.com>wrote:

> PS: Google for H-Eigenfaces (aka Hybrid-Eigenfaces). It is a nifty tweak to
> the original method. A professor in my university just showed me a paper
> that proposes this method, and it greatly solves the problem of pose
> variation.


As we discussed on #digikam, in the paper "Pose invariant virtual classifiers
from single training image using novel
hybrid-eigenfaces" published in
http://linkinghub.elsevier.com/retrieve/pii/S0925231210001475
in page 6, right column, second paragraph it mentions that.
[Quoting]

"It should be noted that the synthesized virtual views would
strictly be under the same pose as H-eigenfaces so only those pose
variations can be obtained in training images which are present in
H-eigenfaces. It is required to have a face dataset consisting of different
subject’s face images under different viewpoints to obtain H-eigenfaces
under those viewpoints.* Consequently, the method relies on the availability
of a generic face dataset
containing face images under different pose*. In this article FERET face
Database [38] serves the purpose of generic dataset."

[/Quoting]

( from the italicized text ) So many pose varied images of a person are
readily available in a face database as FERET but difficult
to get in a Personal Photo album. ( Usage of the system overtime will
increase recognition results but users may not continue
using the system for that long ! )

-- 
regards
-------
Kunal Ghosh
Dept of Computer Sc. & Engineering.
Sir MVIT
Bangalore,India

Quote:
"Ignorance is not a sin, the persistence of ignorance is"
--
"If you find a task difficult today, you'll find it difficult 10yrs later
too !"
-----
"Failing to Plan is Planning to Fail"

Blog:kunalghosh.wordpress.com
Website:www.kunalghosh.net46.net
V-card:http://tinyurl.com/86qjyk
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