ariya presentation at june 22 2011
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8/6/2019 Ariya Presentation at June 22 2011
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Facial Reconstruction from Skull
Ariya Namvong
Advisor: Dr. Rungrote Nilthong
June 22, 2011. Mae Fah Luang University
8/6/2019 Ariya Presentation at June 22 2011
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Overview
Introduction
Facial reconstruction concept
Face dissection
Skull Registration
Face comparing
Reference candidate selection for each part
Example of reconstruction
Conclusion
Discussion
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Facial Reconstruction Concept
Reconstruct face from unknown skull
Dissect skull / face into 4 sections
- orbital / eyes
- nasal / nose- dental / mouth
- remaining part
Search for best candidate for each
section from reference head.
Deform craniometric landmarks from
reference skull into unknown skull
Combine all section together to
produce final result
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Face Dissection
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Skull Registration using Iterative Closest Point (ICP)
All skull have to be registered (align data to the same position and
orientation) before further process.
Minimize the distance between the pair of closest point (one from target
point cloud another one from reference point cloud) by iterative translation
and rotation
Translation: up, down, left, right, front and back
Rotation: pitch, roll and yaw
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Iterative Closest Point - ICP
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Before Registration
Red is point cloud to be registered to green.
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Iterative Closest Point - ICP
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After registration
Red is point cloud to be registered to green.
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Face Comparison ± surface of absolute error
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This comparison based on skull registration. If register face beforecomparing, the result may be different. (unit in mm.)
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Reference candidate selection for each part
In this experiment, face is dissected to 4 parts: eyes, nose, mouth and
remaining
Each part will be selected as reference part considering from skull feature.
- Orbital curve for eyes
- Nasal curve for nose
- Dental surface for mouth
- Remaining point cloud for remaining part
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Orbital Curve
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The best match for orbital curve will be selected as candidate for eyessection.
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Nasal Curve
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The best match for Nasal curve will be selected as candidate for nosesection.
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Dental Surface
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The best match for dental surface will be selected as candidatefor mouth section.
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Remaining Part
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The best match for point cloud of this part will be selected as candidate for remaining section.
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Example: reconstruction of Head 5
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Distance table
Similarity table(considered from distance
table, less distance is more
similarity)
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Result from Rank 1
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Integrate 4 sections from the best match (rank 1)
Target face Rank 1 reconstructed face Error surface
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Result from Rank 2
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Integrate 4 sections from the second best match (rank 2)
Target face Rank 2 reconstructed face Error surface
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Result from Rank 3
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Integrate 4 sections from the rank 3
Target face Rank 3 reconstructed face Error surface
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Result from Rank 1 & 2
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Integrate 4 sections from the rank 1 and rank 2
Target face Rank 1 and 2 reconstructed face Error surface
Reconstruction face from only rank 1 produces too much reference bias, lead to the idea of reconstruction
from more than one reference.
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Result from Rank 1, 2 & 3
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Integrate 4 sections from the rank 1 and rank 2
Target face Rank 1,2 and 3 reconstructed face Error surface
Reconstruction face from only rank 1 produces too much reference bias, lead to the idea of reconstruction
from more than one reference.
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Example: reconstruction of Head 1
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Integrate 4 sections from the rank 1, rank 2 and rank 3
Target face Rank 1,2 and 3 reconstructed face Error surface
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Example: reconstruction of Head 6
This result very different from target face
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Integrate 4 sections from the rank 1, rank 2 and rank 3
Target face Rank 1,2 and 3 reconstructed face Error surface
Nose width incorrect, mouth width incorrect and face shape very different while skull shape not much different
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Conclusions
The best candidate selection method have to be further research
Absolute error surface is just a guideline for evaluation.
There are no evaluation method better than human visual evaluation.
Face shape, nose shape and mouth shape are play important role for
human face recognition. The next research plan have to focus on these.
Some of facial feature does not indicate directly from skull
(have to more further study)
The manual sculpturing knowledge will be added to future research.
(for example: mouth width can be determined from «, nose width can bedetermined from «)
Cephalometric landmarks (facial landmarks) may be added in the future.
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Relation of facial feature and skull
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Wilkinson, C. (2004), Forensic Facial Reconstruction, Cambridge University Press.
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Discussion
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