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Forensics Viz
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Computational Forensics
SC99 exhibit |
The Process
- The unknown skull is matched against a database of known skulls
to build a patchwork skull "twin".
- Then the flesh/skin data from the known skulls
is added to the patchwork skull to create a patchwork reconstruction.
- The
patchwork reconstruction is then morphed to add features (such as eye color)
and make it suitable for rotation.
Problem:
Identification of skeletal remains
Project goal:
Create recognizable (identifiable) facial reconstruction
working from CAT/MRI of unknown skull
Traditional methods:
- Clay reconstruction built on the skull
- 2-D Photographic reconstruction
Advantages to computational reconstruction:
- minimize handling of skull
- 3-d reconstruction can be rotated (enhancing recognition)
- reconstruction can be delivered via web interface
- multiple versions (e.g., different eye colors) can be generated
MRI of researcher
with 24 key points |
Geometric mask with
scalp area removed
and eyeholes added |
Mask morphed to
the 24 points
with eyes added |
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Photo of researcher | |
| Challenge | Solution |
| MRI images do not show hair. This artificial baldness hinders
recognition. Putting in simulated hair that is not correct also hinders
recognition. | The scalp portion of the image is removed, letting the
user mentally fill in an appropriate hairline. |
| MRI image surfaces have many, many triangles, making the image
surface rough and time consuming to render and rotate. |
There are 24 points which are key to facial recognition. These points
are captured from the MRI and mapped onto a smooth geometric mask.
The mask is then morphed to match the 24 points.
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project background |
potential benefits
pilot summary | image gallery
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