Global motion estimation in model-based image coding by trackingthree-dimensional contour feature points
Soo-Chang Pei; Ching-Wen Ko; Ming-Shing Su
Circuits and Systems for Video Technology, IEEE Transactions on
Volume 8, Issue 2, Apr 1998 Page(s):181 - 190
Digital Object Identifier 10.1109/76.664103
Summary:A video coding method called model-based image coding has
attracted much attention as a potential candidate for low bit-rate
visual communication services. This technique reconstructs the facial
image with a preknown 3D human face model and its received model motion
parameters. The parameters of the head motion are mainly divided into
two parts: global motion parameters describe the rigid movement of the
head, such as rotation and translation, and local motion parameters
which deal with the nonrigid movements of facial expressions, such as
the opening and closing of the mouth and eyes. In this paper, we propose
a new approach which can estimate the head global motion more robustly
and accurately. Comparing with the existing techniques to match only a
few key points, here we extract 3-D contour feature points and use
chamfer distance matching to estimate head global motion. This can
improve and enhance the contour tracking performance greatly. We also
develop another technique called facial normalization transform. It maps
the facial region of the current input frame back to the normalized pose
of the initial frame. Using this transform, we can analyze facial
expressions at the same orientation and fixed region. This simplifies
the analysis work a lot. Then, we do our encoding by the clip-and-paste
method along with adaptive codebook technique. In the following the
coder and decoder system are briefly described
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