Abstract
Integral imaging is a three-dimensional (3D) imaging technique that
allows the displaying of full color images with continuous parallax. Its commercial
potential has been increased, due to its ability of presenting to the viewers
smooth 3D images, with full parallax, in a wide viewing zone. Being able to
extract the inherent 3D information from the planar integral images and produce
3D reconstructions, offers advantages in various applications of immersive
entertainment and communications. On this scope, this paper addresses the
problem of accurate depth estimation in integral images. The proposed method,
relying on the assumption that a pixel is the projection of a 3D imaging ray,
aims to specify the first intersection of each pixel's projection ray with
the 3D scene in order to assign to it the corresponding depth value. This
task is formulated as an energy optimization problem and the graph cuts approach
is utilized to solve it. The energy term is twofold; its first part aims to
restrict the desired solution to be close to the observed data, i.e., the
integral image, while the second one enforces regional smoothness in the depth
estimation. This combination offers an accurate and spatially smooth scene
structure. The novelty of the paper lies on the framework's formulation as
one single optimization procedure and on the way that this optimization is
constrained by a set of reliably estimated 3D surface points, called the “anchor
points”. Anchoring the optimization results in enhanced depth estimation
accuracy, while decreasing the optimization processing burden. The proposed
algorithm is evaluated in both synthetic and real integral images consisting
of complicated object scenes. A comparison against other state-of-the-art
algorithms proves the superiority of the proposed method in terms of depth
estimation accuracy.
© 2012 IEEE
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