Hi Pablo,
Can you elaborate a little on your criticism of snakes?
Is the problem:
- That the polyline formulation cannot describe a good solution at all?
- That the size of the state space in the current implementation is
too restrictive?
- That the current implementation's cost functions do not correlate
with a good solution?
- That the current implementation's GDA solver is insufficiently
powerful to find a good answer to the optimization problem?
- something else?
It seems to me that the "best" seamline can be modeled as a polyline,
and the search space can be defined in such a way as to include the
"best" seam as a possibility. I admit that the current search space
definition is a little rough, and that the GDA is buggy and needs
parameter tuning. I think the hard part is defining what is "best" and
turning that into equations. But surely the graph cut approach has
this same requirement?
Andrew
On Sat, Oct 17, 2009 at 10:18 AM, Pablo d'Angelo <pablo.dang...@web.de> wrote:
>
> Hi Andrew,
>
> Andrew Mihal schrieb:
>> Hi,
>> I suspect a problem in the vectorization of the seam lines.
>
> Actually, the approach of using vectorized seam lines is a relatively
> complicated process. Additionally, snakes are not particularly well
> known to find good global solutions. I think a different approach to
> seam line finding would avoid these problems, and also leads to better
> seams. One possibility are the graph cut based segmentation algorithms.
> Here the masks are generated directly and there is no need for going
> from masks to vectors and back to masks. I'm also quite sure that the
> generated seams would be better than with the current snake algorithm.
>
> ciao
> Pablo
>
> >
>
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