Causal Structure and Motion Estimation
The problem of "Structure From Motion" (SFM) deals
with extracting three-dimensional information about the environment from
the motion of its projection onto a two-dimensional surface. The most outstanding
example of machinery to deal with this problem is the combination of the
human eye and brain: from the projection of moving objects onto the retina,
we are able to gather a three-dimensional representation that is sufficient
for us to reach for them, manipulate them, walk around them etc. In engineering,
Control Systems using Vision as a sensor on structured environments
instance freeways or interior of buildings) have recently achieved astonishing
and robustness (see for instance the work of Dickmanns and his coworkers).
However, engineering systems are far from achieving the flexibility
of primates, in that changes of the environment (for instance from a freeway
to a dirt road) require a complete restructuring and reconfiguration of
At the highest level of generality, SFM is an extraordinarily
complicated problem. Most of the research on SFM during the past
20 years has concentrated on a representation of the environment
as a set of points in 3-D space that move rigidly relative to the imaging
surface (the retina or the CCD sensor of a video-camera). The goal of SFM
is then to estimate the 3-D shape and motion of such a collection of feature
points given either the velocity of their perspective projection onto the
imaging sensor (optical flow), or the correspondence between projections
taken from different vantage points (feature correspondence).
|Please see our Virtual Object Insertion page.|
This project is supported by NSF grant IIS-9876145, ARO
grant DAAD19-99-1-0139, and Intel grant 8029.
© 2003 Hailin Jin. All rights reserved.
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Last updated on January 8, 2004.
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