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ROBUST EGO-MOTION ESTIMATION AND 3D MODEL REFINEMENT USING DEPTH BASED PARALLAX MODEL
 

Summary: ROBUST EGO-MOTION ESTIMATION AND 3D MODEL REFINEMENT USING DEPTH
BASED PARALLAX MODEL
Amit K Agrawal and Rama Chellappa
University of Maryland
Department of Electrical and Computer Engineering
College Park, MD 20742 USA
ABSTRACT
We present an iterative algorithm for robustly estimating the ego-
motion and refining and updating a coarse, noisy and partial depth
map using a depth based parallax model and brightness deriva-
tives extracted from an image pair. Given a coarse, noisy and
partial depth map acquired by a range-finder or obtained from a
Digital Elevation Map (DEM), we first estimate the ego-motion by
combining a global ego-motion constraint and a local brightness
constancy constraint. Using the estimated camera motion and the
available depth map estimate, motion of the 3D points is compen-
sated. We utilize the fact that the resulting surface parallax field is
an epipolar field and knowing its direction from the previous mo-
tion estimates, estimate its magnitude and use it to refine the depth
map estimate. Instead of assuming a smooth parallax field or lo-

  

Source: Agrawal, Amit - Mitsubishi Electric Research Labs

 

Collections: Engineering