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Project -
Portable 3D Faces for Field Identification of Suspects
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- Construct a 3D face model based on 2D
images or video captured
by low-resolution surveillance cameras.
- Display a 3D face model with face images rendered at
different
poses, under
various illumination conditions, and with different surroundings so as
to
ease suspect identification.
- Manipulate the 3D face model to create
different facial
expressions,
to simulate the aging process, to add or remove facial hairs, or to
change
hairstyles or other decorations.
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- Stage I: Train generic
(i.e., prior) face
model using many examples:
- 3D mesh model
- Collect
face images from various poses
  
· · · · ·
  
- Gather
subjects' 3D
information by using stereo vision techniques on above poses (or by
using
laser range scans)
- Build generic 3D mesh
- 2D
texture model
- Collect
face image textures for both high and low resolutions
    
    
- Build generic model (e.g., Markov
random
field, MRF) for generating texture's missing high-frequency information.
- 3D mesh & 2D texture
Overlay generic 2D texture
onto generic 3D mesh
- Stage II:
Synthesize face model from single subject's image(s)
- Adapt
generic 3D mesh using
marked points on subject's low-resolution image
- Enhance low-resolution 2D texture
using trained model from Stage I (simulated)
- Overlay enhanced 2D texture onto
adapted 3D mesh
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Any suggestions or comments are
welcome. Please send them to Todd
Stephenson.
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