Abstract
One of the ways by which early human vision is clearly distinguished from current machine vision is the fact that human vision is strongly space variant, and build up a (multiscale) representation of the world from those space variant fixations. In this panel, we will ask how relevant is this principle of human vision to machine vision (Y. Yeshurun), and present the principles of multiscale (C. Guerra) and wavelets (I. DeLotto) approaches that are closely linked to the issue of representation.
This panel discussed some solutions to vision problems based on variable resolution approaches. The pre-defined basis of the discussion included the following hot points:
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1.
Why is foveated vision necessary (if at all.)? or: Should we blindly imitate biological vision?
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2.
What is the preferred type of foveated vision? (e. g. complex log, pyramid)
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3.
What are the effects of foveated vision on customary vision algorithms? (from edge detection to object recognition)
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4.
Effectiveness of multiscale and wavelet techniques.
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References
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© 1994 Springer Science+Business Media New York
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Yeshurun, H., De Lotto, I., Guerra, C. (1994). Panel Summary Foveation, Log-Polar Mapping and Multiscale Approaches to Early Vision. In: Cantoni, V. (eds) Human and Machine Vision. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-1004-2_6
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DOI: https://doi.org/10.1007/978-1-4899-1004-2_6
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4899-1006-6
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