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Foveated visual search for corners
T. Arnow and A. C. Bovik
IEEE Transactions on Image Processing
Abstract
We cast the problem of corner detection as a corner search process. We develop principles of foveated
visual search and automated fixation selection to accomplish the corner search, supplying a case study
of both foveated search and foveated feature detection. The result is a new algorithm for finding corners
which is also a corner-based algorithm for aiming computed foveated visual fixations. In the algorithm,
long saccades move the fovea to previously unexplored areas of the image, while short saccades improve
the accuracy of putative corner locations. The system is tested on two natural scenes. As an interesting
comparison study we compare fixations generated by the algorithm with those of subjects viewing the
same images, whose eye movements are being recorded by an eyetracker. The comparison of fixation
patterns is made using aninformation-theoretic measure. Results show that the algorithm is a good locator
of corners, but does not correlate particularly well with human visual fixations.
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