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Three-dimensional face recognition

delete2005-04-01
delete306
PRE
AI
A
Alexander M. Bronstein
M
Michael M. Bronstein
R
Ron Kimmel
DOI:10.1007/s11263-005-1085-ydelete
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摘要

摘要

En 中文
An expression-invariant 3D face recognition approach is presented. Our basic assumption is that facial expressions can be modelled as isometries of the facial surface. This allows to construct expression-invariant representations of faces using the bending-invariant canonical forms approach. The result is an efficient and accurate face recognition algorithm, robust to facial expressions, that can distinguish between identical twins (the first two authors). We demonstrate a prototype system based on the proposed algorithm and compare its performance to classical face recognition methods. The numerical methods employed by our approach do not require the facial surface explicitly. The surface gradients field, or the surface metric, are sufficient for constructing the expression-invariant representation of any given face. It allows us to perform the 3D face recognition task while avoiding the surface reconstruction stage.
Keyword:
expression-invariant 3D face recognition
isometry invariant
facial expressions
multidimensional scaling
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期刊

International Journal of Computer Vision 封面图
International Journal of Computer Vision
IF:
9.3
论文数:
3.9K
被引数:
2.8W

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