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• W4243675613 abstract "The purpose of this research is to seek evidence for viewer-centered (especially aspect-graph-based) visual processing in the elementary task of object understanding. Two homologous, bilaterally symmetrical three-dimensional (3-D) objects have been employed that differ in that one is based on parts with flat surfaces and the other on parts with curved surfaces. The following procedure has been followed, separately for each object. In the training (saturated free inspection and manipulation) phase, a location (identical for both objects) of the object is marked with a red strip and the subjects' task is to memorize the object structure as well as the position of the strip. In the test phase, two-dimensional views of the object without the strip are presented and the subjects' task is to determine whether the previously marked location should be visible or invisible in the particular view. Findings have been found consistent with an aspect-graph-based 3-D object representation: (a) the reaction times and errors show characteristic dependencies on viewpoint; (b) a number of views (corresponding to certain aspects and aspect transitions of the aspect graph) consistently produce faster and more accurate recognition; (c) the differences in the aspect graphs of the two objects are reflected in differing patterns of reaction times and errors; furthermore; (d) the subjects impose a standard orientation on the objects, whereby a strong inversion effect is observed; and (e) performance varies in a similar way for both objects as a function of tilt. It is concluded that object understanding is viewpoint dependent, that is, based on a number of views. The characteristics of the views found to be most important for object understanding can be employed for creating efficient 3-D object recognition machine vision systems. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 47–72, 2005." @default.
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• W4243675613 date "2005-01-01" @default.
• W4243675613 modified "2023-10-01" @default.
• W4243675613 title "Aspect graphs for three-dimensional object recognition machine vision systems" @default.
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• W4243675613 doi "https://doi.org/10.1002/int.20053" @default.
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