Applications to Post-Attentive Vision - Employing Chaos for Image Registration and Object Tracking
Pp. 233-269 (37)
Michael Edward Farmer
Image registration is a critical upper level vision task for many
applications, as is the related task of object tracking. One of the simplest tracking
algorithms is the correlation tracker which does not require prior object
segmentation to successfully estimate motion parameters of possible objects of
interest. For image registration there are two classes of algorithms, landmark or
point-based and pixel-based. Pixel-based methods are popular in applications where
reliable detection of landmark points is not feasible. As with the other computer
vision tasks defined in the text, the performance of these pixel-based methods is
sensitive to illumination change between the image pair being registered.
Unfortunately illumination change is quite common in image registration problems,
particularly in outdoor scene tracking. The popular measure of Mutual Information
has been widely accepted as the standard measure for image registration; however, it
is sensitive to illumination change. The chaos-based measures such as the Box
Counting dimension and the Information Dimension will be applied to the image
registration problem. The results obtained by these methods will be shown to be
superior to the results provided by the traditional measures.
Registration, mutual information, voxel-based registration.
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