Decoupling object detection and categorization.

We investigated whether there exists a behavioral dependency between object detection and categorization. Previous work (Grill-Spector & Kanwisher, 2005) suggests that object detection and basic-level categorization may be the very same perceptual mechanism: As objects are parsed from the background they are categorized at the basic level. In the current study, we decouple object detection from categorization by manipulating the between-category contrast of the categorization decision. With a superordinate-level contrast with people as one of the target categories (e.g., cars vs. people), which replicates Grill-Spector and Kanwisher, we found that success at object detection depended on success at basic-level categorization and vice versa. But with a basic-level contrast (e.g., cars vs. boats) or superordinate-level contrast without people as a target category (e.g., dog vs. boat), success at object detection did not depend on success at basic-level categorization. Successful object detection could occur without successful basic-level categorization. Object detection and basic-level categorization do not seem to occur within the same early stage of visual processing.

[1]  John K. Kruschke,et al.  Investigations of an Exemplar-Based Connectionist Model of Category Learning , 1992 .

[2]  G. Cottrell,et al.  SOLVING THE VISUAL EXPERTISE MYSTERY , 2004 .

[3]  S. Carey.  Becoming a face expert. , 1992, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[4]  S. Carey,et al.  Why faces are and are not special: an effect of expertise. , 1986 .

[5]  K. Lamberts.  Information-accumulation theory of speeded categorization. , 2000, Psychological review.

[6]  R. Adolphs,et al.  The social brain: neural basis of social knowledge. , 2009, Annual review of psychology.

[7]  T. Poggio,et al.  Hierarchical models of object recognition in cortex , 1999, Nature Neuroscience.

[8]  Michael L. Mack,et al.  Time course of visual object categorization: Fastest does not necessarily mean first , 2009, Vision Research.

[9]  Wayne D. Gray,et al.  Basic objects in natural categories , 1976, Cognitive Psychology.

[10]  J. Mandler,et al.  Separating the sheep from the goats: Differentiating global categories , 1991, Cognitive Psychology.

[11]  Isabel Gauthier,et al.  Object detection and basic-level categorization: Sometimes you know it is there before you know what it is , 2008, Psychonomic bulletin & review.

[12]  Stephen M. Kosslyn,et al.  Pictures and names: Making the connection , 1984, Cognitive Psychology.

[13]  J. Tanaka,et al.  Object categories and expertise: Is the basic level in the eye of the beholder? , 1991, Cognitive Psychology.

[14]  F. Keil,et al.  Efficient visual search by category: Specifying the features that mark the difference between artifacts and animals in preattentive vision , 2001, Perception & psychophysics.

[15]  Thomas J. Palmeri,et al.  An Exemplar-Based Random Walk Model of Speeded Classification , 1997 .

[16]  I. Gauthier,et al.  Unraveling the Time-course of Perceptual Categorization: Does Fastest Mean First? , 2007 .

[17]  Shinsuke Shimojo,et al.  Visual surface representation: a critical link between lower-level and higher level vision , 1995 .

[18]  Christophe L. Labiouse,et al.  Proceedings of the Eighth Neural Computation and Psychology Workshop, Connectionist Models of Cognition and Perception II , 2004 .

[19]  I. Gauthier,et al.  Computational approaches to the development of perceptual expertise , 2004, Trends in Cognitive Sciences.

[20]  Ion Juvina,et al.  Proceedings of the twenty-ninth annual meeting of the cognitive science society , 2007 .

[21]  Jeffrey S. Bowers And,et al.  Short Article: Detecting Objects is Easier than Categorizing Them , 2008, Quarterly journal of experimental psychology.

[22]  T. Palmeri.  Exemplar similarity and the development of automaticity. , 1997, Journal of experimental psychology. Learning, memory, and cognition.

[23]  N. Kanwisher,et al.  PSYCHOLOGICAL SCIENCE Research Article Visual Recognition As Soon as You Know It Is There, You Know What It Is , 2022 .

[24]  James W. Tanaka,et al.  The preferred level of face categorization depends on discriminability , 2008, Psychonomic bulletin & review.

[25]  Isabel Gauthier,et al.  The temporal advantage for individuating objects of expertise: perceptual expertise is an early riser. , 2009, Journal of vision.

[26]  J. Tanaka.  The entry point of face recognition: evidence for face expertise. , 2001, Journal of experimental psychology. General.

[27]  Doris Y. Tsao,et al.  Mechanisms of face perception. , 2008, Annual review of neuroscience.

[28]  Thomas Serre,et al.  A feedforward architecture accounts for rapid categorization , 2007, Proceedings of the National Academy of Sciences.

[29]  M. Tarr,et al.  Becoming a “Greeble” Expert: Exploring Mechanisms for Face Recognition , 1997, Vision Research.

[30]  Elana Zion-Golumbic,et al.  Electrophysiological neural mechanisms for detection, configural analysis and recognition of faces , 2007, NeuroImage.

[31]  N. Kanwisher,et al.  Stages of processing in face perception: an MEG study , 2002, Nature Neuroscience.