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<p class=MsoNormal><font size=2 face=Arial><span lang=EN-GB style='font-size:
10.0pt;font-family:Arial'>Dear List,<o:p></o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span lang=EN-GB style='font-size:
10.0pt;font-family:Arial'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span lang=EN-GB style='font-size:
10.0pt;font-family:Arial'>I’m a research assistant at the Innovation</span></font><font
size=2 face=Arial><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>
Center</span></font><font size=2 face=Arial><span lang=EN-GB style='font-size:
10.0pt;font-family:Arial'> Computer Assisted Surgery (ICCAS) in <st1:place
w:st="on"><st1:City w:st="on">Leipzig</st1:City>, <st1:country-region w:st="on">Germany</st1:country-region></st1:place>.
I’m working on Active Shape Models and Active Appearance Models at the
moment. I’ve discovered two classes of interest for me in vtk. These are:<o:p></o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span lang=EN-GB style='font-size:
10.0pt;font-family:Arial'>vtkPCAAnalysisFilter (Intended for spatially
corresponding points on shape models) and <o:p></o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span lang=EN-GB style='font-size:
10.0pt;font-family:Arial'>vtkPCAStatistics (A more general filter to assess
observations and project those observations in the eigenspace of their
covariance matrix. This is what I use for creating statistical models of
texture, e.g. Active Appearance Models)<o:p></o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span lang=EN-GB style='font-size:
10.0pt;font-family:Arial'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span lang=EN-GB style='font-size:
10.0pt;font-family:Arial'>I was wondering how these two filters cope with incomplete
observations, e.g. missing data components in the observations.<o:p></o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span lang=EN-GB style='font-size:
10.0pt;font-family:Arial'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span lang=EN-GB style='font-size:
10.0pt;font-family:Arial'>Let me illustrate this by an example. If we want to
build a statistical model of an object in an image, say an apple in a
photograph. Assume we have several photos of apples and their respective
segmentations as training data for our model. Further assume some apples are
only contained partially in some of the photos. Statistically speaking, those
apples represent partial observations. I was wondering how to best incorporate those
partial observations in a statistical model which could be built by the two
mentioned vtk filters.<o:p></o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span lang=EN-GB style='font-size:
10.0pt;font-family:Arial'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span lang=EN-GB style='font-size:
10.0pt;font-family:Arial'>Regards,<o:p></o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span lang=EN-GB style='font-size:
10.0pt;font-family:Arial'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span lang=EN-GB style='font-size:
10.0pt;font-family:Arial'>stefan<o:p></o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span lang=EN-GB style='font-size:
10.0pt;font-family:Arial'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=2 face="Times New Roman"><span lang=EN-GB
style='font-size:10.0pt'>_______________________________________________________________________<br>
Dipl. Inform. Stefan Daenzer<br>
Research Associate | Working Group - Scientific Methods<br>
<br>
Universität Leipzig | Faculty of Medicine<br>
<st1:place w:st="on"><st1:PlaceName w:st="on">Innovation</st1:PlaceName> <st1:PlaceType
w:st="on">Center</st1:PlaceType></st1:place> Computer Assisted Surgery (ICCAS)<br>
Semmelweisstr. </span></font><font size=2><span style='font-size:10.0pt'>14<br>
D - 04103 Leipzig<br>
Germany<br>
<br>
Phone: ++49 (0) 341 / 97 - 1 20 03<br>
Fax: ++49 (0) 341 / 97 - 1 20 09<br>
Email: stefan.daenzer@iccas.de</span></font><o:p></o:p></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'><o:p> </o:p></span></font></p>
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