A corpus of 714 full-color images of depth-rotated objects

Abstract

A set of full-color images of objects is described for use in experiments investigating the effects of in-depth rotation on the identification of three-dimensional objects. The corpus contains up to 11 perspective views of 70 nameable objects. We also provide ratings of the "goodness" of each view, based on Thurstonian scaling of subjects' preferences in a paired-comparison experiment. An exploratory cluster analysis on the scaling solutions indicates that the amount of information available in a given view generally is the major determinant of the goodness of the view. For instance, objects with an elongated front-back axis tend to cluster together, and the front and back views of these objects, which do not reveal the object's major surfaces and features, are evaluated as the worst views.