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Abstract

Humans learn and recognize objects through active exploration. Sixteen participants freely
explored 3-D amoeboid objects in a virtual-reality environment during learning. They handled a
device whose spatial coordinates determined the objectlsquo;s position relative to its viewpoint. These
exploration patterns were also recorded for testing. In a subsequent old/new recognition test,
participants either actively explored or passively viewed old (learned) and new objects in the
same setup. Generally, active participants performed better than passive participants (in terms of
sensitivity: d 0 amp;136; 1:08 vs 0.84, respectively). Despite this, those participants who passively viewed
objects animated with their personal motion trajectories for learned objects maintained com-
parable performance to that of participants who actively explored the objects (d 0 amp;136; 1:13). In
contrast, passive observerslsquo; performance decreased when these trajectories were temporally
reversed (d 0 amp;136; 0:69) or when another observerlsquo;s motion trajectories were used (d 0 amp;136; 0:70). While
active exploration generally allowed better recognition of objects compared to passive viewing,
our observers could rely on idiosyncratic exploration patternsöin which particular aspects of
object structure were revealed over timeöto achieve equivalent performance.