English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
Add to Basket
  Local TagsRelease HistoryDetailsSummary

Released
Conference Paper

Face reconstruction using a small set of feature points

MPS-Authors
/persons/resource/persons83815

Blanz,  V
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons84280

Vetter,  T
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

External Resource

https://link.springer.com/content/pdf/10.1007%2F3-540-45482-9_30.pdf
(Publisher version)

Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Hwang, B., Blanz, V., Vetter, T., & Lee, S. (2000). Face reconstruction using a small set of feature points. In S.-W. Lee, H. Bülthoff, & T. Poggio (Eds.), Biologically Motivated Computer Vision: First IEEE International Workshop, BMCV 2000 Seoul, Korea, May 15–17, 2000 (pp. 311-317). Berlin, Germany: Springer.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-E575-6
Abstract
This paper proposes a method for face reconstruction that makes use of only a small set of feature points. Faces can be modeled by forming linear combinations of prototypes of shape and texture information. With the shape and texture information at the feature points alone, we can achieve only an approximation to the deformation required. In such an under-determined condition, we find an optimal solution using a simple least square minimization method. As experimental results, we show well-reconstructed 2D faces even from a small number of feature points.