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要旨:
In this report we present a general introduction to object recognition. We begin with brief discussions of the terminology used in the object recognition literature and the psychophysical tasks that are used to investigate object recognition. We then discuss models of shape representation. We dispense with the idea that shape representations are like the 3-D models used in computer
aided design and explore instead models of shape representation that are based on feature descriptions. As these descriptions encode only the features that are visible from a particular viewpoint, they are generally viewpoint-specific. We discuss various means of achieving viewpoint-invariant recognition using such descriptions, including reliance on diagnostic features visible from a
wide range of viewpoints, storage of multiple descriptions for each object, and the use of transformation mechanisms.
Finally, we discuss how differences in viewpoint dependence that are often observed for within-category and between-category recognition tasks could be due to differences in the types of features that are naturally available to distinguish among different objects in these tasks.
