Alignment by maximization of mutual information
Viola, P.; Wells, W.M., III
Computer Vision, 1995. Proceedings., Fifth International Conference on
Volume , Issue , 20-23 Jun 1995 Page(s):16 - 23
Digital Object Identifier 10.1109/ICCV.1995.466930
Summary:A new information-theoretic approach is presented for finding the
pose of an object in an image. The technique does not require
information about the surface properties of the object, besides its
shape, and is robust with respect to variations of illumination. In our
derivation, few assumptions are made about the nature of the imaging
process. As a result, the algorithms are quite general and can
foreseeably be used in a wide variety of imaging situations. Experiments
are presented that demonstrate the approach in registering magnetic
resonance images, aligning a complex 3D object model to real scenes
including clutter and occlusion, tracking a human head in a video
sequence and aligning a view-based 2D object model to real images. The
method is based on a formulation of the mutual information between the
model and the image. As applied in this paper, the technique is
intensity-based, rather than feature-based. It works well in domains
where edge or gradient-magnitude based methods have difficulty, yet it
is more robust then traditional correlation. Additionally, it has an
efficient implementation that is based on stochastic approximation
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