Abstract:
Human faces are remarkably similar in global
properties, including size, aspect ratio, and location of main features,
but can vary considerably in details across individuals, gender, race,
or due to facial expression. We propose a novel method for 3D shape
recovery of faces that exploits the similarity of
faces. Our method obtains as input a single image and uses a mere single
3D reference model of a different person’s face. Classical
reconstruction methods from single images, i.e. shape-from-shading,
require knowledge of the reflectance properties and lighting as well as
depth values for boundary
conditions. Recent methods circumvent these requirements by representing
input faces as combinations (of hundreds) of stored 3D models. We
propose instead to use the input image as a guide to ”mold” a single
reference model to reach a reconstruction of the sought 3D shape. Our
method assumes Lambertian reflectance and uses harmonic representations
of lighting. It has been tested on images taken under controlled viewing
conditions as well as on uncontrolled images downloaded from the
internet, demonstrating its accuracy and robustness under a variety of
imaging conditions and overcoming significant differences in shape
between the input and reference individuals including differences in
facial expressions, gender and race.
Keywords: 3D, reconstruction, single image, faces, single reference, general images, Lambertian reflectance.
ECCV'06 pdf
Journal version (email me for the preprint) Bibtex
3D Face Reconstruction Examples:
Below are few examples. In each example, you see the input image and our reconstruction results - 3D surface (in pink) and texture. Note the specific details of the individuals (such as wrinkles on Clint Eastwood's face and smile on Tom Hanks), and also the face of Mona Lisa!
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@ARTICLE{KemelmacherBasri_MoldingFaces06, Contact details: For further details please contact: Ira Kemelmacher
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