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dc.contributor.authorRiesenhuber
dc.contributor.authorJarudi
dc.contributor.authorGilad
dc.contributor.authorSinha
dc.date.accessioned2005-12-22T01:20:02Z
dc.date.available2005-12-22T01:20:02Z
dc.date.issued2004-03-05
dc.identifier.otherMIT-CSAIL-TR-2004-010
dc.identifier.otherAIM-2004-006
dc.identifier.otherCBCL-236
dc.identifier.urihttp://hdl.handle.net/1721.1/30451
dc.description.abstractUnderstanding how the human visual system recognizes objects is one of the key challenges in neuroscience. Inspired by a large body of physiological evidence (Felleman and Van Essen, 1991; Hubel and Wiesel, 1962; Livingstone and Hubel, 1988; Tso et al., 2001; Zeki, 1993), a general class of recognition models has emerged which is based on a hierarchical organization of visual processing, with succeeding stages being sensitive to image features of increasing complexity (Hummel and Biederman, 1992; Riesenhuber and Poggio, 1999; Selfridge, 1959). However, these models appear to be incompatible with some well-known psychophysical results. Prominent among these are experiments investigating recognition impairments caused by vertical inversion of images, especially those of faces. It has been reported that faces that differ “featurally” are much easier to distinguish when inverted than those that differ “configurally” (Freire et al., 2000; Le Grand et al., 2001; Mondloch et al., 2002) – a finding that is difficult to reconcile with the aforementioned models. Here we show that after controlling for subjects’ expectations, there is no difference between “featurally” and “configurally” transformed faces in terms of inversion effect. This result reinforces the plausibility of simple hierarchical models of object representation and recognition in cortex.
dc.format.extent12 p.
dc.format.extent14255528 bytes
dc.format.extent840975 bytes
dc.format.mimetypeapplication/postscript
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.relation.ispartofseriesMassachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory
dc.subjectAI
dc.subjectobject recognition
dc.subjectfaces
dc.subjectpsychophysics
dc.subjectinversion effect
dc.subjectneuroscience
dc.subjectcomput
dc.titleFace processing in humans is compatible with a simple shape-based model of vision


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