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Kazuhiko Yokosawa, Hidemichi Mitsumatsu; Contribution of internal details in object recognition. Journal of Vision 2002;2(7):673. doi: 10.1167/2.7.673.
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© ARVO (1962-2015); The Authors (2016-present)
Object recognition becomes difficult when the main axis of the object is foreshortened. This foreshortened disadvantage was greater when the silhouette of the object was presented than when the line drawing of the object was presented (Lawson & Humphreys, 1999). The severe disadvantage in silhouette recognition indicates that the internal detail of the object, which lacks in silhouette, provides useful information, particularly when the main axis is foreshortened. One account is that internal detail contributes to the derivation of the main axis. The other account is that internal detail provides the distinctive features that are directly matched to the object represented in memory. The present study was conducted to test these two accounts. The object presented was either a line drawing or silhouette. The written name of the object was presented before the object. The task was word-object matching. There were two rotational angles of the object: foreshortened (frontal view) and less foreshortened (oblique view). To reduce the uncertainty regarding the axis orientation, in half of the trials, the 3-D arrow indicating the orientation of the main axis was presented as a cue, after the written name, and then the object was presented. The differential foreshortened disadvantage between silhouettes and line drawings was shown in the arrow absence condition. In contrast, the differential foreshortened disadvantage disappeared in the axis present condition. These results indicate that the severe foreshortened disadvantage in silhouette recognition was caused by a lack of axis information. In other words, the internal details provided the information necessary for axis derivation when the axis was foreshortened. These results support the structural description hypothesis, which holds that axis information plays an important role in object recognition.
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