Hierarchical Models of Object Recognition in Cortex-英文文献.pdf

Hierarchical models of object recognition in cortex September 23, 1999 Maximilian Riesenhuber Tomaso Poggio Department of Brain and Cognitive Sciences Center for Biological and Computational Learning and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge, MA 02142 Email: max@ai.mit.edu, tp@ai.mit.edu Address correspondence to T.P. Abstract The classical model of visual processing in cortex is a hierarchy of increasingly sophisticated representations, extending in a natural way the model of simple to complex cells of Hubel and Wiesel. Somewhat surprisingly, little quantitative modeling has been done in the last 15 years to explore the biological feasibility of this class of models to explain higher level visual processing, such as object recognition. We describe a new hierarchical model that accounts well for this complex visual task, is consistent with several recent physiological experiments in inferotemporal cortex and makes testable predictions. The model is based on a novel MAX-like operatio n on the inputs to certain cortical neurons which may have a general role in cortical function. The recognition of visual objects is a fundamental cognitive task performed effortlessly by the brain countless times every day while satisfying two essential requirements: invariance and specificity. In face recognition, for example, we can recognize a specific face among many, while being rather tolerant to changes in viewpoint, scale, illumination, and expression. The brain performs this and sim