A simple method is presented for detecting, localizing and recognizing classes of
objects, while accommodating a wide variation in an object's pose. The method utilizes
a small two-dimensional template that is warped into an image, and converts localization
to a one-dimensional sub-problem, with the search for a match between image and
template executed by dynamic programming. The method recovers three of the six degrees
of freedom of motion (2 translation, 1 rotation), accommodates two more degrees
of freedom in the search process (1 rotation, 1 translation), and is extensible
to the final degree of freedom. Experiments demonstrate that the method provides
an efficient search strategy that outperforms normalized correlation. This is demonstrated
in the example domain of face detection and localization, and is extended to more
general detection tasks. An additional technique recovers a rough object pose from
the match results, and is used in a two stage recognition experiment in conjunction
with maximization of mutual information.
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