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Advances in sensing, signal processing, and computer technology
during the past half century have stimulated numerous attempts to
design general-purpose ma chines that see. These attempts have met
with at best modest success and more typically outright failure.
The difficulties encountered in building working com puter vision
systems based on state-of-the-art techniques came as a surprise.
Perhaps the most frustrating aspect of the problem is that machine
vision sys tems cannot deal with numerous visual tasks that humans
perform rapidly and effortlessly. In reaction to this perceived
discrepancy in performance, various researchers (notably Marr,
1982) suggested that the design of machine-vision systems should be
based on principles drawn from the study of biological systems.
This "neuro morphic" or "anthropomorphic" approach has proven
fruitful: the use of pyramid (multiresolution) image representation
methods in image compression is one ex ample of a successful
application based on principles primarily derived from the study of
biological vision systems. It is still the case, however, that the
perfor of computer vision systems falls far short of that of the
natural systems mance they are intended to mimic, suggesting that
it is time to look even more closely at the remaining differences
between artificial and biological vision systems."
Advances in sensing, signal processing, and computer technology
during the past half century have stimulated numerous attempts to
design general-purpose ma chines that see. These attempts have met
with at best modest success and more typically outright failure.
The difficulties encountered in building working com puter vision
systems based on state-of-the-art techniques came as a surprise.
Perhaps the most frustrating aspect of the problem is that machine
vision sys tems cannot deal with numerous visual tasks that humans
perform rapidly and effortlessly. In reaction to this perceived
discrepancy in performance, various researchers (notably Marr,
1982) suggested that the design of machine-vision systems should be
based on principles drawn from the study of biological systems.
This "neuro morphic" or "anthropomorphic" approach has proven
fruitful: the use of pyramid (multiresolution) image representation
methods in image compression is one ex ample of a successful
application based on principles primarily derived from the study of
biological vision systems. It is still the case, however, that the
perfor of computer vision systems falls far short of that of the
natural systems mance they are intended to mimic, suggesting that
it is time to look even more closely at the remaining differences
between artificial and biological vision systems."
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