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Structure from Motion using the Extended Kalman Filter (Hardcover, 2012)
Loot Price: R2,793
Discovery Miles 27 930
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Structure from Motion using the Extended Kalman Filter (Hardcover, 2012)
Series: Springer Tracts in Advanced Robotics, 75
Expected to ship within 10 - 15 working days
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The fully automated estimation of the 6 degrees of freedom camera
motion and the imaged 3D scenario using as the only input the
pictures taken by the camera has been a long term aim in the
computer vision community. The associated line of research has been
known as Structure from Motion (SfM). An intense research effort
during the latest decades has produced spectacular advances; the
topic has reached a consistent state of maturity and most of its
aspects are well known nowadays. 3D vision has immediate
applications in many and diverse fields like robotics, videogames
and augmented reality; and technological transfer is starting to be
a reality. This book describes one of the first systems for sparse
point-based 3D reconstruction and egomotion estimation from an
image sequence; able to run in real-time at video frame rate and
assuming quite weak prior knowledge about camera calibration,
motion or scene. Its chapters unify the current perspectives of the
robotics and computer vision communities on the 3D vision topic: As
usual in robotics sensing, the explicit estimation and propagation
of the uncertainty hold a central role in the sequential video
processing and is shown to boost the efficiency and performance of
the 3D estimation. On the other hand, some of the most relevant
topics discussed in SfM by the computer vision scientists are
addressed under this probabilistic filtering scheme; namely
projective models, spurious rejection, model selection and
self-calibration.
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