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Registration of a mission video sequence with a reference image
without any meta data (camera location, viewing angles, and
reference DEMs) is still a challenging problem. This paper
presents a layer-based approach to register a video sequence to
a reference image of a 3D scene containing multiple layers.
First, the robust layers from a mission video sequence are
extracted and a layer mosaic is generated for each layer, where
the relative transformation parameters between consecutive
frames are estimated. Then, we formulate the image registration
problem as a region partitioning problem, where the overlapping
regions between two images are partitioned into supporting and
non-supporting (or outlier) regions, and the corresponding
motion parameters are also determined for the supporting
regions. In this approach, we first estimate a set of sparse,
robust correspondences between the first frame and reference
image. Starting from corresponding seed patches, the aligned
areas are expanded to the complete overlapping areas for each
layer using a graph cut algorithm with level set, where the
first frame is registered to the reference image. Then, using
the transformation parameters estimated from the mosaic, we
initially align the remaining frames in the video to the
reference image. Finally, using the same partitioning framework,
the registration is further refined by adjusting the aligned
areas and removing outliers. Several examples are demonstrated
in the experiments to show that our approach is effective and
robust.
Related Publications:
Jiangjian Xiao and Mubarak Shah, “Layer-Based
Video Registration”, Machine Vision and Application,
Vol. 16, No.2, pp. 75-84, 2005.
Jiangjian Xiao, Yunjun Zhang and Mubarak Shah, “Adaptive
Region-Based Video Registration”, IEEE Workshop on
Motion, Jan 5-6, Breckenridge, Colorado, 2005.
Figure 1. Region expansion for initial alignment. (a−b) initial
corresponding patch contours in the reference and mission images
respectively. (c) the final registration result, where the
intensities of the embedded mission image are adjusted by
illumination coefficients. (d) the simple expansion and
partitioning started from the initial contour shown in (a). (e)
the level set representation of the initial contour (a). (f−h)
are intermediate results using the graphcut method with the
level set representation, which can guarantee the expansion
gradually evolves from the center to a boundary. Note: The green
boxes in (a) and (b) are the initial seed regions. (f − h) are
difference images between the warped (b) and (a), and the green
contours in (f − h) are supporting region boundaries obtained
after using bi-partitioning algorithm. The non-supporting pixels
are masked by red.
Figure 2. Video registration results. (a) mission video frames.
(b) registration results for several frames, where the mission
images are superimposed in the reference image. (c) full
registration of all the mission video frames.
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