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ARTICULATED IMPLICIT
SURFACES FOR HUMAN BODY MODELING FROM VIDEO SEQUENCES
In recent years, because cameras have become inexpensive and ever more
prevalent, there has been increasing interest in modeling human shape
and motion from image data. Such an ability has many applications, such
as electronic publishing, entertainment, sports medicine and athletic
training. This, however, is an inherently difficult task, both because
the body is very complex and because the data that can be extracted
from images is often incomplete, noisy and ambiguous.
To overcome these difficulties we start from sophisticated 3-D
animation models and reformulate them so that they can be used for data
analysis. We use them, not only to represent faces and bodies in
motion, but also to guide the interpretation of the image data, thereby
substantially improving performance. Our framework retains the
articulated skeleton of most existing methods but replaces the usual
simple geometric primitives by soft objects. Each primitive defines a
field function and the skin is taken to be a level set of the sum of
these fields. This implicit surface formulation has the following
advantages:
- Effective use of stereo and silhouette data: Defining
surfaces implicitly allows us to define a distance function of data
points to models that is both differentiable and computable without
search.
- Accurate shape description by a small number of
parameters: Varying a few dimensions yields models that can match
different body shapes and allow both shape and motion recovery.
- Explicit modeling of 3--D geometry: Geometry can be
taken into account to predict the expected location of image features
and occluded areas, thereby making the extraction algorithm more
robust.
At the root of our approach is a sophisticated human-body model that
was originally developed solely for animation purposes and that we
reformulated for data analysis purposes.
Results
Click on images for MPEG1 video. Upper
left corner: One of three original video sequences, Upper right corner:
Recovered model in motion, Lower half: Blend of the original sequence
and of the recovered body. Note that the shaded model is overlaid
almost exactly on the real body.
Publications
R. Plaenkers and P. Fua. Articulated
Soft Objects for Multi-View Shape and Motion Capture. IEEE
Transactions on Pattern Analysis and Machine Intelligence, 25(10),
2003.
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