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FGR
2008
IEEE

3D facial geometry recovery via group-wise optical flow

8 years 8 months ago
3D facial geometry recovery via group-wise optical flow
We describe an algorithm for automatically finding correspondences from face video sequences. This method is useful to many applications such as face tracking, face modeling and 3D face recovery. Given a sequence of images, the face feature points are tracked by a model-constraint optical flow algorithm. By employing a Minimum Description Length (MDL) point-refinement framework, the drift-off error caused by the optical flow algorithm can be reduced and the correspondences can be matched robustly by optimizing the statistical model. As a result, the face is able to be tracked precisely. Furthermore, it offers a new method of building an appearance model automatically. The objective root mean square error (RMSE) is used to prove the efficiency of the algorithm. At the same time, the performance is evaluated subjectively by generating 3D face models based upon it.
Hui Fang, Nicholas Costen, David Cristinacce, John
Added 29 May 2010
Updated 29 May 2010
Type Conference
Year 2008
Where FGR
Authors Hui Fang, Nicholas Costen, David Cristinacce, John Darby
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